metadata
license: mit
datasets:
- prabinpanta0/genki_hospital
pipeline_tag: text-classification
tags:
- patient-readmission
- predictive-model
- healthcare
- sklearn
- keras
- LightGBM
language:
- en
model_type: classification
task: patient-readmission-prediction
app_mode: standalone
frameworks:
- scikit-learn
- tensorflow
metrics:
- accuracy
- precision
- recall
- f1
- roc_auc
Patient Readmission Prediction
Tranning
Github: prabinpanta0/Patient-Readmission-Prediction
Dataset
- Original Source: Kaggle/datasets/dubradave/hospital-readmissions
- Import Source: HuggingFace/datasets/prabinpanta0/genki_hospital
{
"model_id": "prabinpanta0/Patient-Readmission-Prediction",
"model_type": "sequence-classification",
"library": {
"random_forest": "scikit-learn",
"logistic_regression": "scikit-learn",
"k_nearest": "scikit-learn",
"svc": "scikit-learn",
"naive_bayes": "scikit-learn",
"neural_network": "keras",
"cross_validation_random_forest": "scikit-learn",
"cross_validation_logistic_regression": "scikit-learn",
"cross_validation_lightgbm": "LightGBM"
},
"model_architectures": {
"random_forest": "RandomForestClassifier",
"logistic_regression": "LogisticRegression",
"k_nearest": "KNeighborsClassifier",
"svc": "SVC",
"naive_bayes": "MultinomialNB",
"neural_network": "NeuralNetwork",
"cross_validation_random_forest": "RandomForestClassifier",
"cross_validation_logistic_regression": "LogisticRegression",
"cross_validation_lightgbm": "LGBMClassifier"
},
"model_paths": {
"random_forest": "model_RandomForestClassifier.pkl",
"logistic_regression": "model_Logistic_Regression.pkl",
"k_nearest": "model_K_nearest.pkl",
"svc": "model_svc.pkl",
"naive_bayes": "model_naive_bayes.pkl",
"neural_network": "neural_network.keras",
"cross_validation_random_forest": "model_rf.pkl",
"cross_validation_logistic_regression": "model_lr.pkl",
"cross_validation_lightgbm": "model_lgbm.pkl"
},
"model_classes": {
"random_forest": "RandomForestClassifier",
"logistic_regression": "LogisticRegression",
"k_nearest": "KNeighborsClassifier",
"svc": "SVC",
"naive_bayes": "MultinomialNB",
"neural_network": "NeuralNetwork",
"cross_validation_random_forest": "RandomForestClassifier",
"cross_validation_logistic_regression": "LogisticRegression"
},
"model_configs": {
"random_forest": {
"n_estimators": 100,
"max_depth": 5
},
"logistic_regression": {
"C": 1,
"max_iter": 1000
},
"k_nearest": {
"n_neighbors": 5
},
"svc": {
"C": 1,
"kernel": "linear"
},
"naive_bayes": {
"alpha": 1
},
"neural_network": {
"input_dim": 10,
"output_dim": 1,
"hidden_dim": 10
},
"cross_validation_random_forest": {
"n_estimators": 100,
"max_depth": 5
},
"cross_validation_logistic_regression": {
"C": 1,
"max_iter": 1000
},
"cross_validation_lightgbm": {
"random_state": 42
}
}
}
metrics
Model | Accuracy | Precision | Recall | AUC-ROC |
---|---|---|---|---|
Random Forest | 0.86544 | 0.8734358240972471 | 0.8337883959044369 | 0.8635809449401703 |
Logistic Regression | 0.74736 | 0.7493540051679587 | 0.6928327645051194 | 0.7441573461079813 |
K-Nearest Neighbors | 0.84112 | 0.8543724844493231 | 0.7969283276450512 | 0.838524404786381 |
Support Vector Classifier | 0.84256 | 0.8492462311557789 | 0.8075085324232082 | 0.8405012541634113 |
Naive Bayes | 0.74176 | 0.7692307692307693 | 0.6416382252559727 | 0.7358793535918418 |
Neural Network | 0.87664 | 0.889009009009009 | 0.8419795221843004 | 0.8746042189234755 |
Random Forest (Cross-Validation) | 0.86544 | 0.8734358240972471 | 0.8337883959044369 | 0.8635809449401703 |
Logistic Regression (Cross-Validation) | 0.74736 | 0.7493540051679587 | 0.6928327645051194 | 0.7441573461079813 |
LightGBM (Cross-Validation) | 0.8728 | 0.8773418168964299 | 0.847098976109215 | 0.8712904519100293 |
Random Forest | Logistic Regression | K-Nearest Neighbors | Support Vector Classifier | Naive Bayes | Neural Network | Random Forest (Cross-Validation) | Logistic Regression (Cross-Validation) | LightGBM (Cross-Validation) |
---|---|---|---|---|---|---|---|---|
1.0 | 0.7453866666666666 | 0.8901866666666667 | 0.8530133333333333 | 0.7455466666666667 | 0.88288 | 1.0 | 0.7453866666666666 | 0.9045866666666667 |
1.0 | 0.7449201741654572 | 0.9005328596802842 | 0.8556024378809189 | 0.7743332882090158 | 0.8964114832535885 | 1.0 | 0.7449201741654572 | 0.910874897792314 |
1.0 | 0.6979827742520399 | 0.8618540344514959 | 0.8272892112420671 | 0.6482320942883046 | 0.849274705349048 | 1.0 | 0.6979827742520399 | 0.8837262012692656 |
1.0 | 0.7427552396345833 | 0.8886139001594574 | 0.8515853672571407 | 0.7401446588709305 | 0.8810145438895148 | 1.0 | 0.7427552396345833 | 0.9034286859660855 |