Update README.md
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README.md
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@@ -40,36 +40,48 @@ train_test_split(df_train,
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random_state=1111)
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##
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```
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Epoch Training Loss Validation Loss
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1 No log 0.
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2 0.
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3 0.
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4 0.
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## Threshold Optimization
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- **Best Threshold:** 0.
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- **F1 @ Threshold:** 0.
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## Eval Results
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```
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precision recall f1-score support
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Alakasiz 0.
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Barinma 0.85 0.
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Elektronik 0.
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Giysi 0.
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Kurtarma 0.86 0.
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Lojistik 0.
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Saglik 0.
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Su 0.
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Yagma 0.
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Yemek 0.
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micro avg 0.
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macro avg 0.
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weighted avg 0.
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samples avg 0.84 0.
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```
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random_state=1111)
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## Class Loss Weights
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- **Alakasiz:** 1.0
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- **Barinma:** 1.5167249178108022
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- **Elektronik:** 1.7547338578655642
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- **Giysi:** 1.9610520059358458
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- **Kurtarma:** 1.269341370129623
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- **Lojistik:** 1.8684086209021484
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- **Saglik:** 1.8019018017117145
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- **Su:** 2.110648663094536
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- **Yagma:** 3.081208739200435
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- **Yemek:** 1.7994815143101963
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## Training Log (Class-Scaled)
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```
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Epoch Training Loss Validation Loss
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1 No log 0.216295
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2 0.260000 0.171498
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3 0.142700 0.175608
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4 0.142700 0.169851
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```
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## Threshold Optimization
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- **Best Threshold:** 0.15
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- **F1 @ Threshold:** 0.7503
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## Eval Results
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```
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precision recall f1-score support
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Alakasiz 0.91 0.87 0.89 734
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Barinma 0.85 0.81 0.83 207
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Elektronik 0.72 0.78 0.75 130
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Giysi 0.73 0.67 0.70 94
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Kurtarma 0.86 0.81 0.83 362
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Lojistik 0.68 0.56 0.62 112
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Saglik 0.72 0.81 0.76 108
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Su 0.61 0.69 0.65 78
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Yagma 0.67 0.65 0.66 31
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Yemek 0.79 0.85 0.82 117
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micro avg 0.82 0.81 0.81 1973
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macro avg 0.75 0.75 0.75 1973
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weighted avg 0.83 0.81 0.81 1973
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samples avg 0.84 0.84 0.83 1973
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```
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