🎯 What I Want to Add
After analyzing the codebase, I found that DsKit lacks comprehensive evaluation functions. I want to add:
- comprehensive_classification_report()
One function that generates:
Confusion matrix heatmap
ROC curve with AUC
Precision-recall curve
Metrics table (precision, recall, F1)
Example:
pythonresults = comprehensive_classification_report(y_test, y_pred, y_proba)
Displays all plots and returns metrics
- regression_evaluation_suite()
One function that generates:
Actual vs Predicted scatter
Residual plots
Q-Q plot
Metrics (MAE, MSE, RMSE, R²)
Example:
pythonresults = regression_evaluation_suite(y_test, y_pred, X_test)
Displays all diagnostic plots and returns metrics
- Testing Infrastructure
The tests/ folder is currently empty. I'll add:
25+ unit tests for the new functions
Test coverage >80%
pytest setup
🎯 What I Want to Add
After analyzing the codebase, I found that DsKit lacks comprehensive evaluation functions. I want to add:
One function that generates:
Confusion matrix heatmap
ROC curve with AUC
Precision-recall curve
Metrics table (precision, recall, F1)
Example:
pythonresults = comprehensive_classification_report(y_test, y_pred, y_proba)
Displays all plots and returns metrics
One function that generates:
Actual vs Predicted scatter
Residual plots
Q-Q plot
Metrics (MAE, MSE, RMSE, R²)
Example:
pythonresults = regression_evaluation_suite(y_test, y_pred, X_test)
Displays all diagnostic plots and returns metrics
The tests/ folder is currently empty. I'll add:
25+ unit tests for the new functions
Test coverage >80%
pytest setup