Cross-Validation Guide

Implement proper cross-validation strategies for reliable model evaluation.

Usage

Describe your dataset and model to get cross-validation recommendations.

Examples

• "Choose a cross-validation strategy for time series data"
• "Implement stratified k-fold for our imbalanced dataset"
• "Set up nested cross-validation for hyperparameter tuning"

Guidelines

• Use stratified k-fold for classification with imbalanced classes
• Never use random splits for time series data
• Use 5 or 10 folds as a standard starting point
• Apply all preprocessing inside the cross-validation loop
• Report mean and standard deviation of cross-validation scores