crossvalind — Generate cross-validation indices and logical train/test partitions.

crossvalind provides MATLAB-compatible cross-validation split helpers for older Statistics and Machine Learning workflows. K-fold calls return numeric fold ids, while holdout, leave-M-out, and resubstitution calls return logical training/test masks.

Syntax

idx = crossvalind('HoldOut', 10, 0.3);

GPU memory and residency

No. crossvalind is a small control-flow/index generation helper. GPU-resident inputs are gathered before partition generation, and outputs are host logical or numeric index arrays.

Examples

Create a reproducible holdout training mask.

rng(2026);
idx = crossvalind('HoldOut', 10, 0.3);
numel(idx)

Assign observations to randomized folds.

rng(1);
fold = crossvalind('KFold', 12, 3);
tabulate(fold)

Preserve class balance when producing a holdout split.

group = [1;1;1;1;2;2;2;2];
[train,test] = crossvalind('HoldOut', 8, 0.5, 'Classes', group);

Using crossvalind with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how crossvalind changes the result.

Related Stats functions

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how crossvalind is executed, line by line, in Rust.

• View the source for crossvalind in Rust on GitHub
• Learn how the RunMat runtime works
• Found a bug? Open an issue with a minimal reproduction.

About RunMat

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