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sign-language-detection – AI Model by Paulie-Aditya | AlphaNeural AI
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sign-language-detection
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Novel Approach 1
Stacked Classifier: RF + SVM + XGB
metrics:
Accuracy: 0.9911734164070612
Balanced Accuracy: 0.9903422714760236
MCC: 0.990784932183338
ROC AUC Score: 0.999934898058849
F1 Score: 0.9911734164070612
Jaccard Score: 0.9825012866700978
Log Loss: 0.033553756349283356
Precision: 0.9911734164070612
Recall: 0.9911734164070612
Novel Approach 2
Stacked Classifier: RF + SVM + KNN + XGB
metrics:
Accuracy: 0.9922118380062306
Balanced Accuracy: 0.9913200369813552
MCC: 0.9918690348004674
ROC AUC Score: 0.9999193482927975
F1 Score: 0.9922118380062306
Jaccard Score: 0.9845440494590417
Log Loss: 0.03136301122428542
Precision: 0.9922118380062306
Recall: 0.9922118380062306
