References

Bundled resources for classification-model-builder skill

model_evaluation_metrics.md: Detailed explanations of various classification model evaluation metrics (accuracy, precision, recall, F1-score, AUC-ROC) and their interpretation.
data_preprocessing_guide.md: Best practices for data preprocessing, including handling missing values, feature scaling, and encoding categorical variables.
model_selection_guide.md: Guidelines for selecting the appropriate classification model based on the characteristics of the dataset and the problem being solved.
hyperparameter_tuning.md: Techniques for hyperparameter tuning to optimize model performance.