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--- |
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pipeline_tag: image-classification |
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tags: |
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- medical |
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--- |
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# Novel Approach 1 |
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## Stacked Classifier: RF + SVM + XGB |
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metrics: |
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- Accuracy: 0.9911734164070612 |
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- Balanced Accuracy: 0.9903422714760236 |
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- MCC: 0.990784932183338 |
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- ROC AUC Score: 0.999934898058849 |
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- F1 Score: 0.9911734164070612 |
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- Jaccard Score: 0.9825012866700978 |
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- Log Loss: 0.033553756349283356 |
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- Precision: 0.9911734164070612 |
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- Recall: 0.9911734164070612 |
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# Novel Approach 2 |
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## Stacked Classifier: RF + SVM + KNN + XGB |
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metrics: |
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- Accuracy: 0.9922118380062306 |
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- Balanced Accuracy: 0.9913200369813552 |
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- MCC: 0.9918690348004674 |
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- ROC AUC Score: 0.9999193482927975 |
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- F1 Score: 0.9922118380062306 |
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- Jaccard Score: 0.9845440494590417 |
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- Log Loss: 0.03136301122428542 |
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- Precision: 0.9922118380062306 |
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- Recall: 0.9922118380062306 |
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