🧑💻: Implement Early Stopping and Confusion Matrix in SVM Implementation (Machine_Learning/SVM) #879
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Title
Implement Early Stopping and Confusion Matrix in SVM Implementation
Enhancement Aim
The aim of this enhancement is to improve the SVM model's training efficiency by incorporating an early stopping mechanism to prevent overfitting, as well as to provide a detailed performance evaluation using a confusion matrix.
Changes
Added logic to stop training if the loss does not improve after a specified number of epochs (patience), reducing unnecessary computations and preventing overfitting.
Integrated the confusion matrix to provide a more granular view of the model's predictions, allowing for better understanding of true positives, true negatives, false positives, and false negatives.
Utilized ConfusionMatrixDisplay from sklearn.metrics for visual representation.
Screenshots 📷
Guidelines
Full Name
SHREYAS SHRENIK PARAJ PATIL
Participant Role
GSSOC CONTRIBUTOR
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