Chart,Question,Id
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (A,B), as 0.",14400
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (not A, B), as 0.",14401
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (A, not B), as 0.",14402
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (not A, not B), as 0.",14403
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (A,B), as 1.",14404
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (not A, B), as 1.",14405
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (A, not B), as 1.",14406
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that Naive Bayes algorithm classifies (not A, not B), as 1.",14407
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 0 for any k ≤ 181.",14408
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 0 for any k ≤ 181.",14409
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 0 for any k ≤ 181.",14410
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 0 for any k ≤ 181.",14411
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 1 for any k ≤ 181.",14412
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 1 for any k ≤ 181.",14413
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 1 for any k ≤ 181.",14414
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 1 for any k ≤ 181.",14415
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 0 for any k ≤ 72.",14416
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 0 for any k ≤ 72.",14417
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 0 for any k ≤ 72.",14418
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 0 for any k ≤ 72.",14419
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 1 for any k ≤ 72.",14420
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 1 for any k ≤ 72.",14421
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 1 for any k ≤ 72.",14422
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 1 for any k ≤ 72.",14423
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 0 for any k ≤ 188.",14424
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 0 for any k ≤ 188.",14425
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 0 for any k ≤ 188.",14426
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 0 for any k ≤ 188.",14427
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 1 for any k ≤ 188.",14428
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 1 for any k ≤ 188.",14429
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 1 for any k ≤ 188.",14430
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 1 for any k ≤ 188.",14431
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 0 for any k ≤ 57.",14432
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 0 for any k ≤ 57.",14433
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 0 for any k ≤ 57.",14434
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 0 for any k ≤ 57.",14435
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A,B) as 1 for any k ≤ 57.",14436
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, B) as 1 for any k ≤ 57.",14437
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (A, not B) as 1 for any k ≤ 57.",14438
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, it is possible to state that KNN algorithm classifies (not A, not B) as 1 for any k ≤ 57.",14439
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (A,B) as 0.",14440
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (not A, B) as 0.",14441
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (A, not B) as 0.",14442
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (not A, not B) as 0.",14443
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (A,B) as 1.",14444
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (not A, B) as 1.",14445
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (A, not B) as 1.",14446
Titanic_decision_tree.png,"Considering that A=True<=>PClass<=2.5 and B=True<=>Parch<=0.5, the Decision Tree presented classifies (not A, not B) as 1.",14447
Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1249 episodes.,14448
Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1416 episodes.,14449
Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1245 episodes.,14450
Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1392 episodes.,14451
Titanic_overfitting_mlp.png,We are able to identify the existence of overfitting for MLP models trained longer than 1232 episodes.,14452
Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 129 estimators.,14453
Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 105 estimators.,14454
Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 86 estimators.,14455
Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 149 estimators.,14456
Titanic_overfitting_gb.png,We are able to identify the existence of overfitting for gradient boosting models with more than 59 estimators.,14457
Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 140 estimators.,14458
Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 57 estimators.,14459
Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 112 estimators.,14460
Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 79 estimators.,14461
Titanic_overfitting_rf.png,We are able to identify the existence of overfitting for random forest models with more than 147 estimators.,14462
Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 2 neighbors.,14463
Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 3 neighbors.,14464
Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 4 neighbors.,14465
Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 5 neighbors.,14466
Titanic_overfitting_knn.png,We are able to identify the existence of overfitting for KNN models with less than 6 neighbors.,14467
Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 2 nodes of depth.,14468
Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 3 nodes of depth.,14469
Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 4 nodes of depth.,14470
Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 5 nodes of depth.,14471
Titanic_overfitting_decision_tree.png,We are able to identify the existence of overfitting for decision tree models with more than 6 nodes of depth.,14472
Titanic_overfitting_rf.png,The random forests results shown can be explained by the lack of diversity resulting from the number of features considered.,14473
Titanic_decision_tree.png,The recall for the presented tree is higher than its accuracy.,14474
Titanic_decision_tree.png,The precision for the presented tree is higher than its accuracy.,14475
Titanic_decision_tree.png,The specificity for the presented tree is higher than its accuracy.,14476
Titanic_decision_tree.png,The recall for the presented tree is lower than its accuracy.,14477
Titanic_decision_tree.png,The precision for the presented tree is lower than its accuracy.,14478
Titanic_decision_tree.png,The specificity for the presented tree is lower than its accuracy.,14479
Titanic_decision_tree.png,The accuracy for the presented tree is higher than its recall.,14480
Titanic_decision_tree.png,The precision for the presented tree is higher than its recall.,14481
Titanic_decision_tree.png,The specificity for the presented tree is higher than its recall.,14482
Titanic_decision_tree.png,The accuracy for the presented tree is lower than its recall.,14483
Titanic_decision_tree.png,The precision for the presented tree is lower than its recall.,14484
Titanic_decision_tree.png,The specificity for the presented tree is lower than its recall.,14485
Titanic_decision_tree.png,The accuracy for the presented tree is higher than its precision.,14486
Titanic_decision_tree.png,The recall for the presented tree is higher than its precision.,14487
Titanic_decision_tree.png,The specificity for the presented tree is higher than its precision.,14488
Titanic_decision_tree.png,The accuracy for the presented tree is lower than its precision.,14489
Titanic_decision_tree.png,The recall for the presented tree is lower than its precision.,14490
Titanic_decision_tree.png,The specificity for the presented tree is lower than its precision.,14491
Titanic_decision_tree.png,The accuracy for the presented tree is higher than its specificity.,14492
Titanic_decision_tree.png,The recall for the presented tree is higher than its specificity.,14493
Titanic_decision_tree.png,The precision for the presented tree is higher than its specificity.,14494
Titanic_decision_tree.png,The accuracy for the presented tree is lower than its specificity.,14495
Titanic_decision_tree.png,The recall for the presented tree is lower than its specificity.,14496
Titanic_decision_tree.png,The precision for the presented tree is lower than its specificity.,14497
Titanic_decision_tree.png,The number of False Positives is higher than the number of True Positives for the presented tree.,14498
Titanic_decision_tree.png,The number of True Negatives is higher than the number of True Positives for the presented tree.,14499
Titanic_decision_tree.png,The number of False Negatives is higher than the number of True Positives for the presented tree.,14500
Titanic_decision_tree.png,The number of False Positives is lower than the number of True Positives for the presented tree.,14501
Titanic_decision_tree.png,The number of True Negatives is lower than the number of True Positives for the presented tree.,14502
Titanic_decision_tree.png,The number of False Negatives is lower than the number of True Positives for the presented tree.,14503
Titanic_decision_tree.png,The number of True Positives is higher than the number of False Positives for the presented tree.,14504
Titanic_decision_tree.png,The number of True Negatives is higher than the number of False Positives for the presented tree.,14505
Titanic_decision_tree.png,The number of False Negatives is higher than the number of False Positives for the presented tree.,14506
Titanic_decision_tree.png,The number of True Positives is lower than the number of False Positives for the presented tree.,14507
Titanic_decision_tree.png,The number of True Negatives is lower than the number of False Positives for the presented tree.,14508
Titanic_decision_tree.png,The number of False Negatives is lower than the number of False Positives for the presented tree.,14509
Titanic_decision_tree.png,The number of True Positives is higher than the number of True Negatives for the presented tree.,14510
Titanic_decision_tree.png,The number of False Positives is higher than the number of True Negatives for the presented tree.,14511
Titanic_decision_tree.png,The number of False Negatives is higher than the number of True Negatives for the presented tree.,14512
Titanic_decision_tree.png,The number of True Positives is lower than the number of True Negatives for the presented tree.,14513
Titanic_decision_tree.png,The number of False Positives is lower than the number of True Negatives for the presented tree.,14514
Titanic_decision_tree.png,The number of False Negatives is lower than the number of True Negatives for the presented tree.,14515
Titanic_decision_tree.png,The number of True Positives is higher than the number of False Negatives for the presented tree.,14516
Titanic_decision_tree.png,The number of False Positives is higher than the number of False Negatives for the presented tree.,14517
Titanic_decision_tree.png,The number of True Negatives is higher than the number of False Negatives for the presented tree.,14518
Titanic_decision_tree.png,The number of True Positives is lower than the number of False Negatives for the presented tree.,14519
Titanic_decision_tree.png,The number of False Positives is lower than the number of False Negatives for the presented tree.,14520
Titanic_decision_tree.png,The number of True Negatives is lower than the number of False Negatives for the presented tree.,14521
Titanic_decision_tree.png,The number of True Positives reported in the same tree is 35.,14522
Titanic_decision_tree.png,The number of False Positives reported in the same tree is 26.,14523
Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 22.,14524
Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 25.,14525
Titanic_decision_tree.png,The number of True Positives reported in the same tree is 50.,14526
Titanic_decision_tree.png,The number of False Positives reported in the same tree is 15.,14527
Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 30.,14528
Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 37.,14529
Titanic_decision_tree.png,The number of True Positives reported in the same tree is 47.,14530
Titanic_decision_tree.png,The number of False Positives reported in the same tree is 19.,14531
Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 40.,14532
Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 12.,14533
Titanic_decision_tree.png,The number of True Positives reported in the same tree is 11.,14534
Titanic_decision_tree.png,The number of False Positives reported in the same tree is 41.,14535
Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 13.,14536
Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 36.,14537
Titanic_decision_tree.png,The number of True Positives reported in the same tree is 18.,14538
Titanic_decision_tree.png,The number of False Positives reported in the same tree is 16.,14539
Titanic_decision_tree.png,The number of True Negatives reported in the same tree is 28.,14540
Titanic_decision_tree.png,The number of False Negatives reported in the same tree is 44.,14541
Titanic_overfitting_dt_acc_rec.png,The difference between recall and accuracy becomes smaller with the depth due to the overfitting phenomenon.,14542
Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 3.,14543
Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 4.,14544
Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 5.,14545
Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 6.,14546
Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 7.,14547
Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 8.,14548
Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 9.,14549
Titanic_overfitting_decision_tree.png,The decision tree is in overfitting for depths above 10.,14550
Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 3.,14551
Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 4.,14552
Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 5.,14553
Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 6.,14554
Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 7.,14555
Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 8.,14556
Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 9.,14557
Titanic_overfitting_decision_tree.png,The chart reporting the recall for different trees shows that the model enters in overfitting for models with depth higher than 10.,14558
Titanic_decision_tree.png,The accuracy for the presented tree is higher than 83%.,14559
Titanic_decision_tree.png,The recall for the presented tree is higher than 82%.,14560
Titanic_decision_tree.png,The precision for the presented tree is higher than 84%.,14561
Titanic_decision_tree.png,The specificity for the presented tree is higher than 85%.,14562
Titanic_decision_tree.png,The accuracy for the presented tree is lower than 62%.,14563
Titanic_decision_tree.png,The recall for the presented tree is lower than 87%.,14564
Titanic_decision_tree.png,The precision for the presented tree is lower than 65%.,14565
Titanic_decision_tree.png,The specificity for the presented tree is lower than 68%.,14566
Titanic_decision_tree.png,The accuracy for the presented tree is higher than 86%.,14567
Titanic_decision_tree.png,The recall for the presented tree is higher than 61%.,14568
Titanic_decision_tree.png,The precision for the presented tree is higher than 81%.,14569
Titanic_decision_tree.png,The specificity for the presented tree is higher than 67%.,14570
Titanic_decision_tree.png,The accuracy for the presented tree is lower than 69%.,14571
Titanic_decision_tree.png,The recall for the presented tree is lower than 88%.,14572
Titanic_decision_tree.png,The precision for the presented tree is lower than 76%.,14573
Titanic_decision_tree.png,The specificity for the presented tree is lower than 73%.,14574
Titanic_decision_tree.png,The accuracy for the presented tree is higher than 60%.,14575
Titanic_decision_tree.png,The recall for the presented tree is higher than 77%.,14576
Titanic_decision_tree.png,The precision for the presented tree is higher than 72%.,14577
Titanic_decision_tree.png,The specificity for the presented tree is higher than 74%.,14578
Titanic_decision_tree.png,The accuracy for the presented tree is lower than 63%.,14579
Titanic_decision_tree.png,The recall for the presented tree is lower than 71%.,14580
Titanic_decision_tree.png,The precision for the presented tree is lower than 79%.,14581
Titanic_decision_tree.png,The specificity for the presented tree is lower than 75%.,14582
Titanic_decision_tree.png,The accuracy for the presented tree is higher than 70%.,14583
Titanic_decision_tree.png,The recall for the presented tree is higher than 64%.,14584
Titanic_decision_tree.png,The precision for the presented tree is higher than 66%.,14585
Titanic_decision_tree.png,The specificity for the presented tree is higher than 78%.,14586
Titanic_decision_tree.png,The accuracy for the presented tree is lower than 89%.,14587
Titanic_decision_tree.png,The recall for the presented tree is lower than 90%.,14588
Titanic_decision_tree.png,The precision for the presented tree is lower than 80%.,14589
Titanic_decision_tree.png,The specificity for the presented tree is lower than 66%.,14590
Titanic_decision_tree.png,The accuracy for the presented tree is higher than 73%.,14591
Titanic_decision_tree.png,The recall for the presented tree is higher than 79%.,14592
Titanic_decision_tree.png,The precision for the presented tree is higher than 62%.,14593
Titanic_decision_tree.png,The specificity for the presented tree is higher than 82%.,14594
Titanic_decision_tree.png,The accuracy for the presented tree is lower than 78%.,14595
Titanic_decision_tree.png,The recall for the presented tree is lower than 64%.,14596
Titanic_decision_tree.png,The precision for the presented tree is lower than 66%.,14597
Titanic_decision_tree.png,The specificity for the presented tree is lower than 89%.,14598
Titanic_overfitting_rf.png,"Results for Random Forests identified as 2, may be explained by its estimators being in underfitting.",14599
Titanic_overfitting_rf.png,"Results for Random Forests identified as 3, may be explained by its estimators being in underfitting.",14600
Titanic_overfitting_rf.png,"Results for Random Forests identified as 10, may be explained by its estimators being in underfitting.",14601
Titanic_overfitting_rf.png,"Results for Random Forests identified as 2, may be explained by its estimators being in overfitting.",14602
Titanic_overfitting_rf.png,"Results for Random Forests identified as 3, may be explained by its estimators being in overfitting.",14603
Titanic_overfitting_rf.png,"Results for Random Forests identified as 10, may be explained by its estimators being in overfitting.",14604
Titanic_overfitting_knn.png,KNN with more than 2 neighbours is in overfitting.,14605
Titanic_overfitting_knn.png,KNN with less than 2 neighbours is in overfitting.,14606
Titanic_overfitting_knn.png,KNN with more than 3 neighbours is in overfitting.,14607
Titanic_overfitting_knn.png,KNN with less than 3 neighbours is in overfitting.,14608
Titanic_overfitting_knn.png,KNN with more than 4 neighbours is in overfitting.,14609
Titanic_overfitting_knn.png,KNN with less than 4 neighbours is in overfitting.,14610
Titanic_overfitting_knn.png,KNN with more than 5 neighbours is in overfitting.,14611
Titanic_overfitting_knn.png,KNN with less than 5 neighbours is in overfitting.,14612
Titanic_overfitting_knn.png,KNN with more than 6 neighbours is in overfitting.,14613
Titanic_overfitting_knn.png,KNN with less than 6 neighbours is in overfitting.,14614
Titanic_overfitting_knn.png,KNN with more than 7 neighbours is in overfitting.,14615
Titanic_overfitting_knn.png,KNN with less than 7 neighbours is in overfitting.,14616
Titanic_overfitting_knn.png,KNN with more than 8 neighbours is in overfitting.,14617
Titanic_overfitting_knn.png,KNN with less than 8 neighbours is in overfitting.,14618
Titanic_overfitting_knn.png,KNN with 1 neighbour is in overfitting.,14619
Titanic_overfitting_knn.png,KNN with 2 neighbour is in overfitting.,14620
Titanic_overfitting_knn.png,KNN with 3 neighbour is in overfitting.,14621
Titanic_overfitting_knn.png,KNN with 4 neighbour is in overfitting.,14622
Titanic_overfitting_knn.png,KNN with 5 neighbour is in overfitting.,14623
Titanic_overfitting_knn.png,KNN with 6 neighbour is in overfitting.,14624
Titanic_overfitting_knn.png,KNN with 7 neighbour is in overfitting.,14625
Titanic_overfitting_knn.png,KNN with 8 neighbour is in overfitting.,14626
Titanic_overfitting_knn.png,KNN with 9 neighbour is in overfitting.,14627
Titanic_overfitting_knn.png,KNN with 10 neighbour is in overfitting.,14628
Titanic_overfitting_knn.png,KNN is in overfitting for k less than 2.,14629
Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 2.,14630
Titanic_overfitting_knn.png,KNN is in overfitting for k less than 3.,14631
Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 3.,14632
Titanic_overfitting_knn.png,KNN is in overfitting for k less than 4.,14633
Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 4.,14634
Titanic_overfitting_knn.png,KNN is in overfitting for k less than 5.,14635
Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 5.,14636
Titanic_overfitting_knn.png,KNN is in overfitting for k less than 6.,14637
Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 6.,14638
Titanic_overfitting_knn.png,KNN is in overfitting for k less than 7.,14639
Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 7.,14640
Titanic_overfitting_knn.png,KNN is in overfitting for k less than 8.,14641
Titanic_overfitting_knn.png,KNN is in overfitting for k larger than 8.,14642
Titanic_decision_tree.png,"As reported in the tree, the number of False Positive is smaller than the number of False Negatives.",14643
Titanic_decision_tree.png,"As reported in the tree, the number of False Positive is bigger than the number of False Negatives.",14644
Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 3 nodes of depth is in overfitting.",14645
Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 4 nodes of depth is in overfitting.",14646
Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 5 nodes of depth is in overfitting.",14647
Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 6 nodes of depth is in overfitting.",14648
Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 7 nodes of depth is in overfitting.",14649
Titanic_overfitting_decision_tree.png,"According to the decision tree overfitting chart, the tree with 8 nodes of depth is in overfitting.",14650
Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 5%.",14651
Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 6%.",14652
Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 7%.",14653
Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 8%.",14654
Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 9%.",14655
Titanic_decision_tree.png,"A smaller tree would be delivered if we would apply post-pruning, accepting an accuracy reduction of 10%.",14656
Titanic_pca.png,Using the first 2 principal components would imply an error between 5 and 20%.,14657
Titanic_pca.png,Using the first 3 principal components would imply an error between 5 and 20%.,14658
Titanic_pca.png,Using the first 4 principal components would imply an error between 5 and 20%.,14659
Titanic_pca.png,Using the first 2 principal components would imply an error between 10 and 20%.,14660
Titanic_pca.png,Using the first 3 principal components would imply an error between 10 and 20%.,14661
Titanic_pca.png,Using the first 4 principal components would imply an error between 10 and 20%.,14662
Titanic_pca.png,Using the first 2 principal components would imply an error between 15 and 20%.,14663
Titanic_pca.png,Using the first 3 principal components would imply an error between 15 and 20%.,14664
Titanic_pca.png,Using the first 4 principal components would imply an error between 15 and 20%.,14665
Titanic_pca.png,Using the first 2 principal components would imply an error between 5 and 25%.,14666
Titanic_pca.png,Using the first 3 principal components would imply an error between 5 and 25%.,14667
Titanic_pca.png,Using the first 4 principal components would imply an error between 5 and 25%.,14668
Titanic_pca.png,Using the first 2 principal components would imply an error between 10 and 25%.,14669
Titanic_pca.png,Using the first 3 principal components would imply an error between 10 and 25%.,14670
Titanic_pca.png,Using the first 4 principal components would imply an error between 10 and 25%.,14671
Titanic_pca.png,Using the first 2 principal components would imply an error between 15 and 25%.,14672
Titanic_pca.png,Using the first 3 principal components would imply an error between 15 and 25%.,14673
Titanic_pca.png,Using the first 4 principal components would imply an error between 15 and 25%.,14674
Titanic_pca.png,Using the first 2 principal components would imply an error between 5 and 30%.,14675
Titanic_pca.png,Using the first 3 principal components would imply an error between 5 and 30%.,14676
Titanic_pca.png,Using the first 4 principal components would imply an error between 5 and 30%.,14677
Titanic_pca.png,Using the first 2 principal components would imply an error between 10 and 30%.,14678
Titanic_pca.png,Using the first 3 principal components would imply an error between 10 and 30%.,14679
Titanic_pca.png,Using the first 4 principal components would imply an error between 10 and 30%.,14680
Titanic_pca.png,Using the first 2 principal components would imply an error between 15 and 30%.,14681
Titanic_pca.png,Using the first 3 principal components would imply an error between 15 and 30%.,14682
Titanic_pca.png,Using the first 4 principal components would imply an error between 15 and 30%.,14683
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Age previously than variable Pclass.,14684
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable SibSp previously than variable Pclass.,14685
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Parch previously than variable Pclass.,14686
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Fare previously than variable Pclass.,14687
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Pclass previously than variable Age.,14688
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable SibSp previously than variable Age.,14689
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Parch previously than variable Age.,14690
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Fare previously than variable Age.,14691
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Pclass previously than variable SibSp.,14692
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Age previously than variable SibSp.,14693
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Parch previously than variable SibSp.,14694
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Fare previously than variable SibSp.,14695
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Pclass previously than variable Parch.,14696
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Age previously than variable Parch.,14697
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable SibSp previously than variable Parch.,14698
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Fare previously than variable Parch.,14699
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Pclass previously than variable Fare.,14700
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Age previously than variable Fare.,14701
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable SibSp previously than variable Fare.,14702
Titanic_correlation_heatmap.png,There is evidence in favour for sequential backward selection to select variable Parch previously than variable Fare.,14703
Titanic_pca.png,The first 2 principal components are enough for explaining half the data variance.,14704
Titanic_pca.png,The first 3 principal components are enough for explaining half the data variance.,14705
Titanic_pca.png,The first 4 principal components are enough for explaining half the data variance.,14706
Titanic_boxplots.png,Scaling this dataset would be mandatory to improve the results with distance-based methods.,14707
Titanic_correlation_heatmap.png,Removing variable Pclass might improve the training of decision trees .,14708
Titanic_correlation_heatmap.png,Removing variable Age might improve the training of decision trees .,14709
Titanic_correlation_heatmap.png,Removing variable SibSp might improve the training of decision trees .,14710
Titanic_correlation_heatmap.png,Removing variable Parch might improve the training of decision trees .,14711
Titanic_correlation_heatmap.png,Removing variable Fare might improve the training of decision trees .,14712
Titanic_histograms.png,"Not knowing the semantics of Pclass variable, dummification could have been a more adequate codification.",14713
Titanic_histograms.png,"Not knowing the semantics of Sex variable, dummification could have been a more adequate codification.",14714
Titanic_histograms.png,"Not knowing the semantics of Age variable, dummification could have been a more adequate codification.",14715
Titanic_histograms.png,"Not knowing the semantics of SibSp variable, dummification could have been a more adequate codification.",14716
Titanic_histograms.png,"Not knowing the semantics of Parch variable, dummification could have been a more adequate codification.",14717
Titanic_histograms.png,"Not knowing the semantics of Fare variable, dummification could have been a more adequate codification.",14718
Titanic_histograms.png,"Not knowing the semantics of Embarked variable, dummification could have been a more adequate codification.",14719
Titanic_boxplots.png,Normalization of this dataset could not have impact on a KNN classifier.,14720
Titanic_boxplots.png,"Multiplying ratio and Boolean variables by 100, and variables with a range between 0 and 10 by 10, would have an impact similar to other scaling transformations.",14721
Titanic_histograms.png,It is better to drop the variable Pclass than removing all records with missing values.,14722
Titanic_histograms.png,It is better to drop the variable Sex than removing all records with missing values.,14723
Titanic_histograms.png,It is better to drop the variable Age than removing all records with missing values.,14724
Titanic_histograms.png,It is better to drop the variable SibSp than removing all records with missing values.,14725
Titanic_histograms.png,It is better to drop the variable Parch than removing all records with missing values.,14726
Titanic_histograms.png,It is better to drop the variable Fare than removing all records with missing values.,14727
Titanic_histograms.png,It is better to drop the variable Embarked than removing all records with missing values.,14728
Titanic_histograms.png,"Given the usual semantics of Pclass variable, dummification would have been a better codification.",14729
Titanic_histograms.png,"Given the usual semantics of Sex variable, dummification would have been a better codification.",14730
Titanic_histograms.png,"Given the usual semantics of Age variable, dummification would have been a better codification.",14731
Titanic_histograms.png,"Given the usual semantics of SibSp variable, dummification would have been a better codification.",14732
Titanic_histograms.png,"Given the usual semantics of Parch variable, dummification would have been a better codification.",14733
Titanic_histograms.png,"Given the usual semantics of Fare variable, dummification would have been a better codification.",14734
Titanic_histograms.png,"Given the usual semantics of Embarked variable, dummification would have been a better codification.",14735
Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Pclass seems to be promising.",14736
Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Pclass seems to be promising.",14737
Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Pclass seems to be promising.",14738
Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Pclass seems to be promising.",14739
Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Pclass seems to be promising.",14740
Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Pclass seems to be promising.",14741
Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Sex seems to be promising.",14742
Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Sex seems to be promising.",14743
Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Sex seems to be promising.",14744
Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Sex seems to be promising.",14745
Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Sex seems to be promising.",14746
Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Sex seems to be promising.",14747
Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Age seems to be promising.",14748
Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Age seems to be promising.",14749
Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Age seems to be promising.",14750
Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Age seems to be promising.",14751
Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Age seems to be promising.",14752
Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Age seems to be promising.",14753
Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of SibSp seems to be promising.",14754
Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of SibSp seems to be promising.",14755
Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of SibSp seems to be promising.",14756
Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of SibSp seems to be promising.",14757
Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of SibSp seems to be promising.",14758
Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of SibSp seems to be promising.",14759
Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Parch seems to be promising.",14760
Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Parch seems to be promising.",14761
Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Parch seems to be promising.",14762
Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Parch seems to be promising.",14763
Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Parch seems to be promising.",14764
Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Parch seems to be promising.",14765
Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Fare seems to be promising.",14766
Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Fare seems to be promising.",14767
Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Fare seems to be promising.",14768
Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Fare seems to be promising.",14769
Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Fare seems to be promising.",14770
Titanic_histograms.png,"Feature generation based on the use of variable Embarked wouldn’t be useful, but the use of Fare seems to be promising.",14771
Titanic_histograms.png,"Feature generation based on the use of variable Pclass wouldn’t be useful, but the use of Embarked seems to be promising.",14772
Titanic_histograms.png,"Feature generation based on the use of variable Sex wouldn’t be useful, but the use of Embarked seems to be promising.",14773
Titanic_histograms.png,"Feature generation based on the use of variable Age wouldn’t be useful, but the use of Embarked seems to be promising.",14774
Titanic_histograms.png,"Feature generation based on the use of variable SibSp wouldn’t be useful, but the use of Embarked seems to be promising.",14775
Titanic_histograms.png,"Feature generation based on the use of variable Parch wouldn’t be useful, but the use of Embarked seems to be promising.",14776
Titanic_histograms.png,"Feature generation based on the use of variable Fare wouldn’t be useful, but the use of Embarked seems to be promising.",14777
Titanic_histograms.png,Feature generation based on both variables Sex and Pclass seems to be promising.,14778
Titanic_histograms.png,Feature generation based on both variables Age and Pclass seems to be promising.,14779
Titanic_histograms.png,Feature generation based on both variables SibSp and Pclass seems to be promising.,14780
Titanic_histograms.png,Feature generation based on both variables Parch and Pclass seems to be promising.,14781
Titanic_histograms.png,Feature generation based on both variables Fare and Pclass seems to be promising.,14782
Titanic_histograms.png,Feature generation based on both variables Embarked and Pclass seems to be promising.,14783
Titanic_histograms.png,Feature generation based on both variables Pclass and Sex seems to be promising.,14784
Titanic_histograms.png,Feature generation based on both variables Age and Sex seems to be promising.,14785
Titanic_histograms.png,Feature generation based on both variables SibSp and Sex seems to be promising.,14786
Titanic_histograms.png,Feature generation based on both variables Parch and Sex seems to be promising.,14787
Titanic_histograms.png,Feature generation based on both variables Fare and Sex seems to be promising.,14788
Titanic_histograms.png,Feature generation based on both variables Embarked and Sex seems to be promising.,14789
Titanic_histograms.png,Feature generation based on both variables Pclass and Age seems to be promising.,14790
Titanic_histograms.png,Feature generation based on both variables Sex and Age seems to be promising.,14791
Titanic_histograms.png,Feature generation based on both variables SibSp and Age seems to be promising.,14792
Titanic_histograms.png,Feature generation based on both variables Parch and Age seems to be promising.,14793
Titanic_histograms.png,Feature generation based on both variables Fare and Age seems to be promising.,14794
Titanic_histograms.png,Feature generation based on both variables Embarked and Age seems to be promising.,14795
Titanic_histograms.png,Feature generation based on both variables Pclass and SibSp seems to be promising.,14796
Titanic_histograms.png,Feature generation based on both variables Sex and SibSp seems to be promising.,14797
Titanic_histograms.png,Feature generation based on both variables Age and SibSp seems to be promising.,14798
Titanic_histograms.png,Feature generation based on both variables Parch and SibSp seems to be promising.,14799
Titanic_histograms.png,Feature generation based on both variables Fare and SibSp seems to be promising.,14800
Titanic_histograms.png,Feature generation based on both variables Embarked and SibSp seems to be promising.,14801
Titanic_histograms.png,Feature generation based on both variables Pclass and Parch seems to be promising.,14802
Titanic_histograms.png,Feature generation based on both variables Sex and Parch seems to be promising.,14803
Titanic_histograms.png,Feature generation based on both variables Age and Parch seems to be promising.,14804
Titanic_histograms.png,Feature generation based on both variables SibSp and Parch seems to be promising.,14805
Titanic_histograms.png,Feature generation based on both variables Fare and Parch seems to be promising.,14806
Titanic_histograms.png,Feature generation based on both variables Embarked and Parch seems to be promising.,14807
Titanic_histograms.png,Feature generation based on both variables Pclass and Fare seems to be promising.,14808
Titanic_histograms.png,Feature generation based on both variables Sex and Fare seems to be promising.,14809
Titanic_histograms.png,Feature generation based on both variables Age and Fare seems to be promising.,14810
Titanic_histograms.png,Feature generation based on both variables SibSp and Fare seems to be promising.,14811
Titanic_histograms.png,Feature generation based on both variables Parch and Fare seems to be promising.,14812
Titanic_histograms.png,Feature generation based on both variables Embarked and Fare seems to be promising.,14813
Titanic_histograms.png,Feature generation based on both variables Pclass and Embarked seems to be promising.,14814
Titanic_histograms.png,Feature generation based on both variables Sex and Embarked seems to be promising.,14815
Titanic_histograms.png,Feature generation based on both variables Age and Embarked seems to be promising.,14816
Titanic_histograms.png,Feature generation based on both variables SibSp and Embarked seems to be promising.,14817
Titanic_histograms.png,Feature generation based on both variables Parch and Embarked seems to be promising.,14818
Titanic_histograms.png,Feature generation based on both variables Fare and Embarked seems to be promising.,14819
Titanic_mv.png,There is no reason to believe that discarding records showing missing values is safer than discarding the corresponding variables in this case.,14820
Titanic_mv.png,Dropping all rows with missing values can lead to a dataset with less than 25% of the original data.,14821
Titanic_mv.png,Dropping all rows with missing values can lead to a dataset with less than 30% of the original data.,14822
Titanic_mv.png,Dropping all rows with missing values can lead to a dataset with less than 40% of the original data.,14823
Titanic_mv.png,Dropping all records with missing values would be better than to drop the variables with missing values.,14824
Titanic_mv.png,Discarding variables Sex and Pclass would be better than discarding all the records with missing values for those variables.,14825
Titanic_mv.png,Discarding variables Age and Pclass would be better than discarding all the records with missing values for those variables.,14826
Titanic_mv.png,Discarding variables SibSp and Pclass would be better than discarding all the records with missing values for those variables.,14827
Titanic_mv.png,Discarding variables Parch and Pclass would be better than discarding all the records with missing values for those variables.,14828
Titanic_mv.png,Discarding variables Fare and Pclass would be better than discarding all the records with missing values for those variables.,14829
Titanic_mv.png,Discarding variables Embarked and Pclass would be better than discarding all the records with missing values for those variables.,14830
Titanic_mv.png,Discarding variables Pclass and Sex would be better than discarding all the records with missing values for those variables.,14831
Titanic_mv.png,Discarding variables Age and Sex would be better than discarding all the records with missing values for those variables.,14832
Titanic_mv.png,Discarding variables SibSp and Sex would be better than discarding all the records with missing values for those variables.,14833
Titanic_mv.png,Discarding variables Parch and Sex would be better than discarding all the records with missing values for those variables.,14834
Titanic_mv.png,Discarding variables Fare and Sex would be better than discarding all the records with missing values for those variables.,14835
Titanic_mv.png,Discarding variables Embarked and Sex would be better than discarding all the records with missing values for those variables.,14836
Titanic_mv.png,Discarding variables Pclass and Age would be better than discarding all the records with missing values for those variables.,14837
Titanic_mv.png,Discarding variables Sex and Age would be better than discarding all the records with missing values for those variables.,14838
Titanic_mv.png,Discarding variables SibSp and Age would be better than discarding all the records with missing values for those variables.,14839
Titanic_mv.png,Discarding variables Parch and Age would be better than discarding all the records with missing values for those variables.,14840
Titanic_mv.png,Discarding variables Fare and Age would be better than discarding all the records with missing values for those variables.,14841
Titanic_mv.png,Discarding variables Embarked and Age would be better than discarding all the records with missing values for those variables.,14842
Titanic_mv.png,Discarding variables Pclass and SibSp would be better than discarding all the records with missing values for those variables.,14843
Titanic_mv.png,Discarding variables Sex and SibSp would be better than discarding all the records with missing values for those variables.,14844
Titanic_mv.png,Discarding variables Age and SibSp would be better than discarding all the records with missing values for those variables.,14845
Titanic_mv.png,Discarding variables Parch and SibSp would be better than discarding all the records with missing values for those variables.,14846
Titanic_mv.png,Discarding variables Fare and SibSp would be better than discarding all the records with missing values for those variables.,14847
Titanic_mv.png,Discarding variables Embarked and SibSp would be better than discarding all the records with missing values for those variables.,14848
Titanic_mv.png,Discarding variables Pclass and Parch would be better than discarding all the records with missing values for those variables.,14849
Titanic_mv.png,Discarding variables Sex and Parch would be better than discarding all the records with missing values for those variables.,14850
Titanic_mv.png,Discarding variables Age and Parch would be better than discarding all the records with missing values for those variables.,14851
Titanic_mv.png,Discarding variables SibSp and Parch would be better than discarding all the records with missing values for those variables.,14852
Titanic_mv.png,Discarding variables Fare and Parch would be better than discarding all the records with missing values for those variables.,14853
Titanic_mv.png,Discarding variables Embarked and Parch would be better than discarding all the records with missing values for those variables.,14854
Titanic_mv.png,Discarding variables Pclass and Fare would be better than discarding all the records with missing values for those variables.,14855
Titanic_mv.png,Discarding variables Sex and Fare would be better than discarding all the records with missing values for those variables.,14856
Titanic_mv.png,Discarding variables Age and Fare would be better than discarding all the records with missing values for those variables.,14857
Titanic_mv.png,Discarding variables SibSp and Fare would be better than discarding all the records with missing values for those variables.,14858
Titanic_mv.png,Discarding variables Parch and Fare would be better than discarding all the records with missing values for those variables.,14859
Titanic_mv.png,Discarding variables Embarked and Fare would be better than discarding all the records with missing values for those variables.,14860
Titanic_mv.png,Discarding variables Pclass and Embarked would be better than discarding all the records with missing values for those variables.,14861
Titanic_mv.png,Discarding variables Sex and Embarked would be better than discarding all the records with missing values for those variables.,14862
Titanic_mv.png,Discarding variables Age and Embarked would be better than discarding all the records with missing values for those variables.,14863
Titanic_mv.png,Discarding variables SibSp and Embarked would be better than discarding all the records with missing values for those variables.,14864
Titanic_mv.png,Discarding variables Parch and Embarked would be better than discarding all the records with missing values for those variables.,14865
Titanic_mv.png,Discarding variables Fare and Embarked would be better than discarding all the records with missing values for those variables.,14866
Titanic_histograms.png,The variable Pclass can be coded as ordinal without losing information.,14867
Titanic_histograms.png,The variable Sex can be coded as ordinal without losing information.,14868
Titanic_histograms.png,The variable Age can be coded as ordinal without losing information.,14869
Titanic_histograms.png,The variable SibSp can be coded as ordinal without losing information.,14870
Titanic_histograms.png,The variable Parch can be coded as ordinal without losing information.,14871
Titanic_histograms.png,The variable Fare can be coded as ordinal without losing information.,14872
Titanic_histograms.png,The variable Embarked can be coded as ordinal without losing information.,14873
Titanic_histograms.png,"Considering the common semantics for Pclass variable, dummification would be the most adequate encoding.",14874
Titanic_histograms.png,"Considering the common semantics for Sex variable, dummification would be the most adequate encoding.",14875
Titanic_histograms.png,"Considering the common semantics for Age variable, dummification would be the most adequate encoding.",14876
Titanic_histograms.png,"Considering the common semantics for SibSp variable, dummification would be the most adequate encoding.",14877
Titanic_histograms.png,"Considering the common semantics for Parch variable, dummification would be the most adequate encoding.",14878
Titanic_histograms.png,"Considering the common semantics for Fare variable, dummification would be the most adequate encoding.",14879
Titanic_histograms.png,"Considering the common semantics for Embarked variable, dummification would be the most adequate encoding.",14880
Titanic_histograms.png,"Considering the common semantics for Sex and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14881
Titanic_histograms.png,"Considering the common semantics for Age and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14882
Titanic_histograms.png,"Considering the common semantics for SibSp and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14883
Titanic_histograms.png,"Considering the common semantics for Parch and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14884
Titanic_histograms.png,"Considering the common semantics for Fare and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14885
Titanic_histograms.png,"Considering the common semantics for Embarked and Pclass variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14886
Titanic_histograms.png,"Considering the common semantics for Pclass and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14887
Titanic_histograms.png,"Considering the common semantics for Age and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14888
Titanic_histograms.png,"Considering the common semantics for SibSp and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14889
Titanic_histograms.png,"Considering the common semantics for Parch and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14890
Titanic_histograms.png,"Considering the common semantics for Fare and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14891
Titanic_histograms.png,"Considering the common semantics for Embarked and Sex variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14892
Titanic_histograms.png,"Considering the common semantics for Pclass and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14893
Titanic_histograms.png,"Considering the common semantics for Sex and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14894
Titanic_histograms.png,"Considering the common semantics for SibSp and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14895
Titanic_histograms.png,"Considering the common semantics for Parch and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14896
Titanic_histograms.png,"Considering the common semantics for Fare and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14897
Titanic_histograms.png,"Considering the common semantics for Embarked and Age variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14898
Titanic_histograms.png,"Considering the common semantics for Pclass and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14899
Titanic_histograms.png,"Considering the common semantics for Sex and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14900
Titanic_histograms.png,"Considering the common semantics for Age and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14901
Titanic_histograms.png,"Considering the common semantics for Parch and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14902
Titanic_histograms.png,"Considering the common semantics for Fare and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14903
Titanic_histograms.png,"Considering the common semantics for Embarked and SibSp variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14904
Titanic_histograms.png,"Considering the common semantics for Pclass and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14905
Titanic_histograms.png,"Considering the common semantics for Sex and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14906
Titanic_histograms.png,"Considering the common semantics for Age and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14907
Titanic_histograms.png,"Considering the common semantics for SibSp and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14908
Titanic_histograms.png,"Considering the common semantics for Fare and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14909
Titanic_histograms.png,"Considering the common semantics for Embarked and Parch variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14910
Titanic_histograms.png,"Considering the common semantics for Pclass and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14911
Titanic_histograms.png,"Considering the common semantics for Sex and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14912
Titanic_histograms.png,"Considering the common semantics for Age and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14913
Titanic_histograms.png,"Considering the common semantics for SibSp and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14914
Titanic_histograms.png,"Considering the common semantics for Parch and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14915
Titanic_histograms.png,"Considering the common semantics for Embarked and Fare variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14916
Titanic_histograms.png,"Considering the common semantics for Pclass and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14917
Titanic_histograms.png,"Considering the common semantics for Sex and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14918
Titanic_histograms.png,"Considering the common semantics for Age and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14919
Titanic_histograms.png,"Considering the common semantics for SibSp and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14920
Titanic_histograms.png,"Considering the common semantics for Parch and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14921
Titanic_histograms.png,"Considering the common semantics for Fare and Embarked variables, dummification if applied would increase the risk of facing the curse of dimensionality.",14922
Titanic_class_histogram.png,Balancing this dataset would be mandatory to improve the results.,14923
Titanic_nr_records_nr_variables.png,Balancing this dataset by SMOTE would most probably be preferable over undersampling.,14924
Titanic_scatter-plots.png,Balancing this dataset by SMOTE would be riskier than oversampling by replication.,14925
Titanic_correlation_heatmap.png,"Applying a non-supervised feature selection based on the redundancy, would not increase the performance of the generality of the training algorithms in this dataset.",14926
Titanic_boxplots.png,"A scaling transformation is mandatory, in order to improve the Naive Bayes performance in this dataset.",14927
Titanic_boxplots.png,"A scaling transformation is mandatory, in order to improve the  KNN performance in this dataset.",14928
Titanic_correlation_heatmap.png,Variables Age and Pclass seem to be useful for classification tasks.,14929
Titanic_correlation_heatmap.png,Variables SibSp and Pclass seem to be useful for classification tasks.,14930
Titanic_correlation_heatmap.png,Variables Parch and Pclass seem to be useful for classification tasks.,14931
Titanic_correlation_heatmap.png,Variables Fare and Pclass seem to be useful for classification tasks.,14932
Titanic_correlation_heatmap.png,Variables Pclass and Age seem to be useful for classification tasks.,14933
Titanic_correlation_heatmap.png,Variables SibSp and Age seem to be useful for classification tasks.,14934
Titanic_correlation_heatmap.png,Variables Parch and Age seem to be useful for classification tasks.,14935
Titanic_correlation_heatmap.png,Variables Fare and Age seem to be useful for classification tasks.,14936
Titanic_correlation_heatmap.png,Variables Pclass and SibSp seem to be useful for classification tasks.,14937
Titanic_correlation_heatmap.png,Variables Age and SibSp seem to be useful for classification tasks.,14938
Titanic_correlation_heatmap.png,Variables Parch and SibSp seem to be useful for classification tasks.,14939
Titanic_correlation_heatmap.png,Variables Fare and SibSp seem to be useful for classification tasks.,14940
Titanic_correlation_heatmap.png,Variables Pclass and Parch seem to be useful for classification tasks.,14941
Titanic_correlation_heatmap.png,Variables Age and Parch seem to be useful for classification tasks.,14942
Titanic_correlation_heatmap.png,Variables SibSp and Parch seem to be useful for classification tasks.,14943
Titanic_correlation_heatmap.png,Variables Fare and Parch seem to be useful for classification tasks.,14944
Titanic_correlation_heatmap.png,Variables Pclass and Fare seem to be useful for classification tasks.,14945
Titanic_correlation_heatmap.png,Variables Age and Fare seem to be useful for classification tasks.,14946
Titanic_correlation_heatmap.png,Variables SibSp and Fare seem to be useful for classification tasks.,14947
Titanic_correlation_heatmap.png,Variables Parch and Fare seem to be useful for classification tasks.,14948
Titanic_correlation_heatmap.png,Variable Pclass seems to be relevant for the majority of mining tasks.,14949
Titanic_correlation_heatmap.png,Variable Age seems to be relevant for the majority of mining tasks.,14950
Titanic_correlation_heatmap.png,Variable SibSp seems to be relevant for the majority of mining tasks.,14951
Titanic_correlation_heatmap.png,Variable Parch seems to be relevant for the majority of mining tasks.,14952
Titanic_correlation_heatmap.png,Variable Fare seems to be relevant for the majority of mining tasks.,14953
Titanic_decision_tree.png,Variable Pclass is one of the most relevant variables.,14954
Titanic_decision_tree.png,Variable Age is one of the most relevant variables.,14955
Titanic_decision_tree.png,Variable SibSp is one of the most relevant variables.,14956
Titanic_decision_tree.png,Variable Parch is one of the most relevant variables.,14957
Titanic_decision_tree.png,Variable Fare is one of the most relevant variables.,14958
Titanic_decision_tree.png,It is possible to state that Pclass is the first most discriminative variable regarding the class.,14959
Titanic_decision_tree.png,It is possible to state that Age is the first most discriminative variable regarding the class.,14960
Titanic_decision_tree.png,It is possible to state that SibSp is the first most discriminative variable regarding the class.,14961
Titanic_decision_tree.png,It is possible to state that Parch is the first most discriminative variable regarding the class.,14962
Titanic_decision_tree.png,It is possible to state that Fare is the first most discriminative variable regarding the class.,14963
Titanic_decision_tree.png,It is possible to state that Pclass is the second most discriminative variable regarding the class.,14964
Titanic_decision_tree.png,It is possible to state that Age is the second most discriminative variable regarding the class.,14965
Titanic_decision_tree.png,It is possible to state that SibSp is the second most discriminative variable regarding the class.,14966
Titanic_decision_tree.png,It is possible to state that Parch is the second most discriminative variable regarding the class.,14967
Titanic_decision_tree.png,It is possible to state that Fare is the second most discriminative variable regarding the class.,14968
Titanic_decision_tree.png,"The variable Pclass discriminates between the target values, as shown in the decision tree.",14969
Titanic_decision_tree.png,"The variable Age discriminates between the target values, as shown in the decision tree.",14970
Titanic_decision_tree.png,"The variable SibSp discriminates between the target values, as shown in the decision tree.",14971
Titanic_decision_tree.png,"The variable Parch discriminates between the target values, as shown in the decision tree.",14972
Titanic_decision_tree.png,"The variable Fare discriminates between the target values, as shown in the decision tree.",14973
Titanic_decision_tree.png,The variable Pclass seems to be one of the two most relevant features.,14974
Titanic_decision_tree.png,The variable Age seems to be one of the two most relevant features.,14975
Titanic_decision_tree.png,The variable SibSp seems to be one of the two most relevant features.,14976
Titanic_decision_tree.png,The variable Parch seems to be one of the two most relevant features.,14977
Titanic_decision_tree.png,The variable Fare seems to be one of the two most relevant features.,14978
Titanic_decision_tree.png,The variable Pclass seems to be one of the three most relevant features.,14979
Titanic_decision_tree.png,The variable Age seems to be one of the three most relevant features.,14980
Titanic_decision_tree.png,The variable SibSp seems to be one of the three most relevant features.,14981
Titanic_decision_tree.png,The variable Parch seems to be one of the three most relevant features.,14982
Titanic_decision_tree.png,The variable Fare seems to be one of the three most relevant features.,14983
Titanic_decision_tree.png,The variable Pclass seems to be one of the four most relevant features.,14984
Titanic_decision_tree.png,The variable Age seems to be one of the four most relevant features.,14985
Titanic_decision_tree.png,The variable SibSp seems to be one of the four most relevant features.,14986
Titanic_decision_tree.png,The variable Parch seems to be one of the four most relevant features.,14987
Titanic_decision_tree.png,The variable Fare seems to be one of the four most relevant features.,14988
Titanic_decision_tree.png,The variable Pclass seems to be one of the five most relevant features.,14989
Titanic_decision_tree.png,The variable Age seems to be one of the five most relevant features.,14990
Titanic_decision_tree.png,The variable SibSp seems to be one of the five most relevant features.,14991
Titanic_decision_tree.png,The variable Parch seems to be one of the five most relevant features.,14992
Titanic_decision_tree.png,The variable Fare seems to be one of the five most relevant features.,14993
Titanic_decision_tree.png,It is clear that variable Pclass is one of the two most relevant features.,14994
Titanic_decision_tree.png,It is clear that variable Age is one of the two most relevant features.,14995
Titanic_decision_tree.png,It is clear that variable SibSp is one of the two most relevant features.,14996
Titanic_decision_tree.png,It is clear that variable Parch is one of the two most relevant features.,14997
Titanic_decision_tree.png,It is clear that variable Fare is one of the two most relevant features.,14998
Titanic_decision_tree.png,It is clear that variable Pclass is one of the three most relevant features.,14999
Titanic_decision_tree.png,It is clear that variable Age is one of the three most relevant features.,15000
Titanic_decision_tree.png,It is clear that variable SibSp is one of the three most relevant features.,15001
Titanic_decision_tree.png,It is clear that variable Parch is one of the three most relevant features.,15002
Titanic_decision_tree.png,It is clear that variable Fare is one of the three most relevant features.,15003
Titanic_decision_tree.png,It is clear that variable Pclass is one of the four most relevant features.,15004
Titanic_decision_tree.png,It is clear that variable Age is one of the four most relevant features.,15005
Titanic_decision_tree.png,It is clear that variable SibSp is one of the four most relevant features.,15006
Titanic_decision_tree.png,It is clear that variable Parch is one of the four most relevant features.,15007
Titanic_decision_tree.png,It is clear that variable Fare is one of the four most relevant features.,15008
Titanic_decision_tree.png,It is clear that variable Pclass is one of the five most relevant features.,15009
Titanic_decision_tree.png,It is clear that variable Age is one of the five most relevant features.,15010
Titanic_decision_tree.png,It is clear that variable SibSp is one of the five most relevant features.,15011
Titanic_decision_tree.png,It is clear that variable Parch is one of the five most relevant features.,15012
Titanic_decision_tree.png,It is clear that variable Fare is one of the five most relevant features.,15013
Titanic_correlation_heatmap.png,"From the correlation analysis alone, it is clear that there are relevant variables.",15014
Titanic_correlation_heatmap.png,Variables Age and Pclass are redundant.,15015
Titanic_correlation_heatmap.png,Variables SibSp and Pclass are redundant.,15016
Titanic_correlation_heatmap.png,Variables Parch and Pclass are redundant.,15017
Titanic_correlation_heatmap.png,Variables Fare and Pclass are redundant.,15018
Titanic_correlation_heatmap.png,Variables Pclass and Age are redundant.,15019
Titanic_correlation_heatmap.png,Variables SibSp and Age are redundant.,15020
Titanic_correlation_heatmap.png,Variables Parch and Age are redundant.,15021
Titanic_correlation_heatmap.png,Variables Fare and Age are redundant.,15022
Titanic_correlation_heatmap.png,Variables Pclass and SibSp are redundant.,15023
Titanic_correlation_heatmap.png,Variables Age and SibSp are redundant.,15024
Titanic_correlation_heatmap.png,Variables Parch and SibSp are redundant.,15025
Titanic_correlation_heatmap.png,Variables Fare and SibSp are redundant.,15026
Titanic_correlation_heatmap.png,Variables Pclass and Parch are redundant.,15027
Titanic_correlation_heatmap.png,Variables Age and Parch are redundant.,15028
Titanic_correlation_heatmap.png,Variables SibSp and Parch are redundant.,15029
Titanic_correlation_heatmap.png,Variables Fare and Parch are redundant.,15030
Titanic_correlation_heatmap.png,Variables Pclass and Fare are redundant.,15031
Titanic_correlation_heatmap.png,Variables Age and Fare are redundant.,15032
Titanic_correlation_heatmap.png,Variables SibSp and Fare are redundant.,15033
Titanic_correlation_heatmap.png,Variables Parch and Fare are redundant.,15034
Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Sex and SibSp.",15035
Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Sex and Fare.",15036
Titanic_correlation_heatmap.png,"Variables Parch and Fare are redundant, but we can’t say the same for the pair Sex and Embarked.",15037
Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Pclass and Fare.",15038
Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Fare and Embarked.",15039
Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Sex and Age.",15040
Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Sex and Parch.",15041
Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Sex and Parch.",15042
Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Age and Embarked.",15043
Titanic_correlation_heatmap.png,"Variables Sex and Age are redundant, but we can’t say the same for the pair Fare and Embarked.",15044
Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Age and SibSp.",15045
Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Pclass and Age.",15046
Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair SibSp and Fare.",15047
Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Sex and SibSp.",15048
Titanic_correlation_heatmap.png,"Variables Sex and Age are redundant, but we can’t say the same for the pair SibSp and Parch.",15049
Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Age and Fare.",15050
Titanic_correlation_heatmap.png,"Variables Sex and SibSp are redundant, but we can’t say the same for the pair Age and Embarked.",15051
Titanic_correlation_heatmap.png,"Variables Sex and Parch are redundant, but we can’t say the same for the pair Age and SibSp.",15052
Titanic_correlation_heatmap.png,"Variables Sex and Fare are redundant, but we can’t say the same for the pair Pclass and Embarked.",15053
Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Age and Fare.",15054
Titanic_correlation_heatmap.png,"Variables Pclass and Parch are redundant, but we can’t say the same for the pair Sex and SibSp.",15055
Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair SibSp and Parch.",15056
Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Parch and Fare.",15057
Titanic_correlation_heatmap.png,"Variables Age and SibSp are redundant, but we can’t say the same for the pair Sex and Parch.",15058
Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Age and Embarked.",15059
Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Parch and Embarked.",15060
Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair SibSp and Fare.",15061
Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Parch and Fare.",15062
Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Age and Embarked.",15063
Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Sex and Embarked.",15064
Titanic_correlation_heatmap.png,"Variables Pclass and Age are redundant, but we can’t say the same for the pair Sex and SibSp.",15065
Titanic_correlation_heatmap.png,"Variables Parch and Embarked are redundant, but we can’t say the same for the pair Sex and SibSp.",15066
Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair Pclass and Fare.",15067
Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Age and SibSp.",15068
Titanic_correlation_heatmap.png,"Variables Parch and Fare are redundant, but we can’t say the same for the pair Sex and SibSp.",15069
Titanic_correlation_heatmap.png,"Variables Pclass and Age are redundant, but we can’t say the same for the pair SibSp and Fare.",15070
Titanic_correlation_heatmap.png,"Variables Pclass and Parch are redundant, but we can’t say the same for the pair SibSp and Embarked.",15071
Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Parch and Embarked.",15072
Titanic_correlation_heatmap.png,"Variables Age and SibSp are redundant, but we can’t say the same for the pair Parch and Embarked.",15073
Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Age and Parch.",15074
Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Sex and Fare.",15075
Titanic_correlation_heatmap.png,"Variables Age and Fare are redundant, but we can’t say the same for the pair Pclass and SibSp.",15076
Titanic_correlation_heatmap.png,"Variables Sex and Embarked are redundant, but we can’t say the same for the pair Pclass and Age.",15077
Titanic_correlation_heatmap.png,"Variables Parch and Embarked are redundant, but we can’t say the same for the pair Sex and Age.",15078
Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Sex and Age.",15079
Titanic_correlation_heatmap.png,"Variables Pclass and Parch are redundant, but we can’t say the same for the pair Sex and Fare.",15080
Titanic_correlation_heatmap.png,"Variables Sex and Age are redundant, but we can’t say the same for the pair SibSp and Embarked.",15081
Titanic_correlation_heatmap.png,"Variables Sex and Embarked are redundant, but we can’t say the same for the pair Pclass and Fare.",15082
Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair Sex and SibSp.",15083
Titanic_correlation_heatmap.png,"Variables Sex and Parch are redundant, but we can’t say the same for the pair Age and Fare.",15084
Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Pclass and Age.",15085
Titanic_correlation_heatmap.png,"Variables Pclass and Parch are redundant, but we can’t say the same for the pair Fare and Embarked.",15086
Titanic_correlation_heatmap.png,"Variables Pclass and Age are redundant, but we can’t say the same for the pair Sex and Parch.",15087
Titanic_correlation_heatmap.png,"Variables Age and Fare are redundant, but we can’t say the same for the pair SibSp and Embarked.",15088
Titanic_correlation_heatmap.png,"Variables SibSp and Embarked are redundant, but we can’t say the same for the pair Age and Fare.",15089
Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Pclass and Embarked.",15090
Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Age and Parch.",15091
Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Pclass and Fare.",15092
Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair Pclass and SibSp.",15093
Titanic_correlation_heatmap.png,"Variables Parch and Embarked are redundant, but we can’t say the same for the pair Pclass and Fare.",15094
Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Pclass and Sex.",15095
Titanic_correlation_heatmap.png,"Variables Pclass and Embarked are redundant, but we can’t say the same for the pair Sex and Fare.",15096
Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Age and SibSp.",15097
Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Pclass and SibSp.",15098
Titanic_correlation_heatmap.png,"Variables Sex and Parch are redundant, but we can’t say the same for the pair Age and Embarked.",15099
Titanic_correlation_heatmap.png,"Variables Age and Parch are redundant, but we can’t say the same for the pair Sex and Fare.",15100
Titanic_correlation_heatmap.png,"Variables Parch and Fare are redundant, but we can’t say the same for the pair Pclass and Age.",15101
Titanic_correlation_heatmap.png,"Variables Sex and SibSp are redundant, but we can’t say the same for the pair Pclass and Age.",15102
Titanic_correlation_heatmap.png,"Variables Pclass and Fare are redundant, but we can’t say the same for the pair Age and SibSp.",15103
Titanic_correlation_heatmap.png,"Variables Sex and Embarked are redundant, but we can’t say the same for the pair SibSp and Fare.",15104
Titanic_correlation_heatmap.png,"Variables Fare and Embarked are redundant, but we can’t say the same for the pair Sex and Age.",15105
Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Pclass and Embarked.",15106
Titanic_correlation_heatmap.png,"Variables SibSp and Fare are redundant, but we can’t say the same for the pair Sex and Age.",15107
Titanic_correlation_heatmap.png,"Variables SibSp and Parch are redundant, but we can’t say the same for the pair Pclass and Age.",15108
Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Age and Parch.",15109
Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Fare and Embarked.",15110
Titanic_correlation_heatmap.png,"Variables Pclass and Age are redundant, but we can’t say the same for the pair Fare and Embarked.",15111
Titanic_correlation_heatmap.png,"Variables Pclass and Sex are redundant, but we can’t say the same for the pair Parch and Fare.",15112
Titanic_correlation_heatmap.png,"Variables Pclass and SibSp are redundant, but we can’t say the same for the pair Sex and Fare.",15113
Titanic_correlation_heatmap.png,"Variables Sex and Age are redundant, but we can’t say the same for the pair Pclass and Fare.",15114
Titanic_correlation_heatmap.png,"Variables Pclass and Fare are redundant, but we can’t say the same for the pair Age and Embarked.",15115
Titanic_correlation_heatmap.png,"Variables Age and Embarked are redundant, but we can’t say the same for the pair Sex and Parch.",15116
Titanic_correlation_heatmap.png,"Variables Age and Parch are redundant, but we can’t say the same for the pair Fare and Embarked.",15117
Titanic_correlation_heatmap.png,"Variables Sex and Fare are redundant, but we can’t say the same for the pair SibSp and Parch.",15118
Titanic_correlation_heatmap.png,The variable Pclass can be discarded without risking losing information.,15119
Titanic_correlation_heatmap.png,The variable Age can be discarded without risking losing information.,15120
Titanic_correlation_heatmap.png,The variable SibSp can be discarded without risking losing information.,15121
Titanic_correlation_heatmap.png,The variable Parch can be discarded without risking losing information.,15122
Titanic_correlation_heatmap.png,The variable Fare can be discarded without risking losing information.,15123
Titanic_correlation_heatmap.png,One of the variables Age or Pclass can be discarded without losing information.,15124
Titanic_correlation_heatmap.png,One of the variables SibSp or Pclass can be discarded without losing information.,15125
Titanic_correlation_heatmap.png,One of the variables Parch or Pclass can be discarded without losing information.,15126
Titanic_correlation_heatmap.png,One of the variables Fare or Pclass can be discarded without losing information.,15127
Titanic_correlation_heatmap.png,One of the variables Pclass or Age can be discarded without losing information.,15128
Titanic_correlation_heatmap.png,One of the variables SibSp or Age can be discarded without losing information.,15129
Titanic_correlation_heatmap.png,One of the variables Parch or Age can be discarded without losing information.,15130
Titanic_correlation_heatmap.png,One of the variables Fare or Age can be discarded without losing information.,15131
Titanic_correlation_heatmap.png,One of the variables Pclass or SibSp can be discarded without losing information.,15132
Titanic_correlation_heatmap.png,One of the variables Age or SibSp can be discarded without losing information.,15133
Titanic_correlation_heatmap.png,One of the variables Parch or SibSp can be discarded without losing information.,15134
Titanic_correlation_heatmap.png,One of the variables Fare or SibSp can be discarded without losing information.,15135
Titanic_correlation_heatmap.png,One of the variables Pclass or Parch can be discarded without losing information.,15136
Titanic_correlation_heatmap.png,One of the variables Age or Parch can be discarded without losing information.,15137
Titanic_correlation_heatmap.png,One of the variables SibSp or Parch can be discarded without losing information.,15138
Titanic_correlation_heatmap.png,One of the variables Fare or Parch can be discarded without losing information.,15139
Titanic_correlation_heatmap.png,One of the variables Pclass or Fare can be discarded without losing information.,15140
Titanic_correlation_heatmap.png,One of the variables Age or Fare can be discarded without losing information.,15141
Titanic_correlation_heatmap.png,One of the variables SibSp or Fare can be discarded without losing information.,15142
Titanic_correlation_heatmap.png,One of the variables Parch or Fare can be discarded without losing information.,15143
Titanic_histograms_numeric.png,The existence of outliers is one of the problems to tackle in this dataset.,15144
Titanic_boxplots.png,The boxplots presented show a large number of outliers for most of the numeric variables.,15145
Titanic_boxplots.png,The histograms presented show a large number of outliers for most of the numeric variables.,15146
Titanic_histograms_numeric.png,At least 50 of the variables present outliers.,15147
Titanic_boxplots.png,At least 60 of the variables present outliers.,15148
Titanic_histograms_numeric.png,At least 75 of the variables present outliers.,15149
Titanic_histograms_numeric.png,At least 85 of the variables present outliers.,15150
Titanic_boxplots.png,Variable Pclass presents some outliers.,15151
Titanic_histograms_numeric.png,Variable Age presents some outliers.,15152
Titanic_boxplots.png,Variable SibSp presents some outliers.,15153
Titanic_boxplots.png,Variable Parch presents some outliers.,15154
Titanic_histograms_numeric.png,Variable Fare presents some outliers.,15155
Titanic_boxplots.png,Variable Pclass doesn’t have any outliers.,15156
Titanic_histograms_numeric.png,Variable Age doesn’t have any outliers.,15157
Titanic_histograms_numeric.png,Variable SibSp doesn’t have any outliers.,15158
Titanic_boxplots.png,Variable Parch doesn’t have any outliers.,15159
Titanic_boxplots.png,Variable Fare doesn’t have any outliers.,15160
Titanic_histograms_numeric.png,Variable Pclass shows some outlier values.,15161
Titanic_boxplots.png,Variable Age shows some outlier values.,15162
Titanic_histograms_numeric.png,Variable SibSp shows some outlier values.,15163
Titanic_boxplots.png,Variable Parch shows some outlier values.,15164
Titanic_histograms_numeric.png,Variable Fare shows some outlier values.,15165
Titanic_boxplots.png,Variable Pclass shows a high number of outlier values.,15166
Titanic_histograms_numeric.png,Variable Age shows a high number of outlier values.,15167
Titanic_boxplots.png,Variable SibSp shows a high number of outlier values.,15168
Titanic_histograms_numeric.png,Variable Parch shows a high number of outlier values.,15169
Titanic_boxplots.png,Variable Fare shows a high number of outlier values.,15170
Titanic_histograms_numeric.png,Outliers seem to be a problem in the dataset.,15171
Titanic_histograms_numeric.png,"It is clear that variable Age shows some outliers, but we can’t be sure of the same for variable Pclass.",15172
Titanic_boxplots.png,"It is clear that variable SibSp shows some outliers, but we can’t be sure of the same for variable Pclass.",15173
Titanic_histograms_numeric.png,"It is clear that variable Parch shows some outliers, but we can’t be sure of the same for variable Pclass.",15174
Titanic_boxplots.png,"It is clear that variable Fare shows some outliers, but we can’t be sure of the same for variable Pclass.",15175
Titanic_boxplots.png,"It is clear that variable Pclass shows some outliers, but we can’t be sure of the same for variable Age.",15176
Titanic_boxplots.png,"It is clear that variable SibSp shows some outliers, but we can’t be sure of the same for variable Age.",15177
Titanic_histograms_numeric.png,"It is clear that variable Parch shows some outliers, but we can’t be sure of the same for variable Age.",15178
Titanic_histograms_numeric.png,"It is clear that variable Fare shows some outliers, but we can’t be sure of the same for variable Age.",15179
Titanic_boxplots.png,"It is clear that variable Pclass shows some outliers, but we can’t be sure of the same for variable SibSp.",15180
Titanic_boxplots.png,"It is clear that variable Age shows some outliers, but we can’t be sure of the same for variable SibSp.",15181
Titanic_histograms_numeric.png,"It is clear that variable Parch shows some outliers, but we can’t be sure of the same for variable SibSp.",15182
Titanic_boxplots.png,"It is clear that variable Fare shows some outliers, but we can’t be sure of the same for variable SibSp.",15183
Titanic_histograms_numeric.png,"It is clear that variable Pclass shows some outliers, but we can’t be sure of the same for variable Parch.",15184
Titanic_histograms_numeric.png,"It is clear that variable Age shows some outliers, but we can’t be sure of the same for variable Parch.",15185
Titanic_boxplots.png,"It is clear that variable SibSp shows some outliers, but we can’t be sure of the same for variable Parch.",15186
Titanic_boxplots.png,"It is clear that variable Fare shows some outliers, but we can’t be sure of the same for variable Parch.",15187
Titanic_histograms_numeric.png,"It is clear that variable Pclass shows some outliers, but we can’t be sure of the same for variable Fare.",15188
Titanic_histograms_numeric.png,"It is clear that variable Age shows some outliers, but we can’t be sure of the same for variable Fare.",15189
Titanic_histograms_numeric.png,"It is clear that variable SibSp shows some outliers, but we can’t be sure of the same for variable Fare.",15190
Titanic_histograms_numeric.png,"It is clear that variable Parch shows some outliers, but we can’t be sure of the same for variable Fare.",15191
Titanic_boxplots.png,Those boxplots show that the data is not normalized.,15192
Titanic_boxplots.png,Variable Pclass is balanced.,15193
Titanic_histograms_numeric.png,Variable Age is balanced.,15194
Titanic_boxplots.png,Variable SibSp is balanced.,15195
Titanic_histograms_numeric.png,Variable Parch is balanced.,15196
Titanic_histograms_numeric.png,Variable Fare is balanced.,15197
Titanic_histograms.png,The variable Pclass can be seen as ordinal without losing information.,15198
Titanic_histograms.png,The variable Sex can be seen as ordinal without losing information.,15199
Titanic_histograms.png,The variable Age can be seen as ordinal without losing information.,15200
Titanic_histograms.png,The variable SibSp can be seen as ordinal without losing information.,15201
Titanic_histograms.png,The variable Parch can be seen as ordinal without losing information.,15202
Titanic_histograms.png,The variable Fare can be seen as ordinal without losing information.,15203
Titanic_histograms.png,The variable Embarked can be seen as ordinal without losing information.,15204
Titanic_histograms.png,The variable Pclass can be seen as ordinal.,15205
Titanic_histograms.png,The variable Sex can be seen as ordinal.,15206
Titanic_histograms.png,The variable Age can be seen as ordinal.,15207
Titanic_histograms.png,The variable SibSp can be seen as ordinal.,15208
Titanic_histograms.png,The variable Parch can be seen as ordinal.,15209
Titanic_histograms.png,The variable Fare can be seen as ordinal.,15210
Titanic_histograms.png,The variable Embarked can be seen as ordinal.,15211
Titanic_histograms.png,"All variables, but the class, should be dealt with as numeric.",15212
Titanic_histograms.png,"All variables, but the class, should be dealt with as binary.",15213
Titanic_histograms.png,"All variables, but the class, should be dealt with as date.",15214
Titanic_histograms.png,"All variables, but the class, should be dealt with as symbolic.",15215
Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 50.,15216
Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 93.,15217
Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 47.,15218
Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 12.,15219
Titanic_correlation_heatmap.png,The intrinsic dimensionality of this dataset is 38.,15220
Titanic_nr_records_nr_variables.png,We face the curse of dimensionality when training a classifier with this dataset.,15221
Titanic_nr_records_nr_variables.png,"Given the number of records and that some variables are numeric, we might be facing the curse of dimensionality.",15222
Titanic_nr_records_nr_variables.png,"Given the number of records and that some variables are binary, we might be facing the curse of dimensionality.",15223
Titanic_nr_records_nr_variables.png,"Given the number of records and that some variables are date, we might be facing the curse of dimensionality.",15224
Titanic_nr_records_nr_variables.png,"Given the number of records and that some variables are symbolic, we might be facing the curse of dimensionality.",15225