K-Fold Cross-Validation Code | Dataford Interview Questions

Can you write a code snippet to perform k-fold cross-validation?

Implement k_fold_split(n_samples, k, shuffle, seed) using only Python's standard library. Return k pairs of training and validation index lists, with every sample used exactly once for validation. Validation folds should be as balanced as possible, and shuffling must be reproducible when a seed is provided. For example, n_samples = 5, k = 2, shuffle = False returns validation folds of sizes 3 and 2.

Constraints

1 <= n_samples <= 10000
2 <= k <= n_samples
0 <= seed <= 10^9
shuffle is a boolean
Training and validation indices in each split must be disjoint
Every sample must appear in exactly one validation fold

Function Signature

def k_fold_split(n_samples, k, shuffle, seed):

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Problem

Can you write a code snippet to perform k-fold cross-validation?

Constraints

1 <= n_samples <= 10000
2 <= k <= n_samples
0 <= seed <= 10^9
shuffle is a boolean
Training and validation indices in each split must be disjoint
Every sample must appear in exactly one validation fold

Function Signature

def k_fold_split(n_samples, k, shuffle, seed):

Your question is K-Fold Cross-Validation Code. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.