K-Fold Cross Validation
Validation & Tuning DS practice problem on Onlearn.
Difficulty: medium.
Topics: Understanding Implement K-Fold Cross-Validation, K-Fold Indices, Hold-out Set, Stratification, Leave-One-Out Cross-Validation, Data Shuffling, Model Evaluation & Selection, Statistical Learning Theory, Data Preprocessing, Algorithmic Complexity, Software Engineering for ML, Resampling Methods, Bias-Variance Tradeoff, Data Partitioning Strategies, Performance Metrics, Iterative Model Validation.
Implement a function to generate train and test splits for K Fold Cross Validation. Your task is to divide the dataset into k folds and return a list of train test indices for each fold.