php-ml/docs/machine-learning/cross-validation/stratified-random-split.md

Stratified Random Split

Analogously to RandomSpilt class, samples are split to two groups: train group and test group. Distribution of samples takes into account their targets and trying to divide them equally. You can adjust the number of samples in each group.

Constructor Parameters

• $dataset - object that implements Dataset interface
• $testSize - a fraction of test split (float, from 0 to 1, default: 0.3)
• $seed - seed for random generator (e.g. for tests)

$split = new StratifiedRandomSplit($dataset, 0.2);

Samples and labels groups

To get samples or labels from test and train group, you can use getters:

$dataset = new StratifiedRandomSplit($dataset, 0.3, 1234);

// train group
$dataset->getTrainSamples();
$dataset->getTrainLabels();

// test group
$dataset->getTestSamples();
$dataset->getTestLabels();

Example

$dataset = new ArrayDataset(
    $samples = [[1], [2], [3], [4], [5], [6], [7], [8]],
    $targets = ['a', 'a', 'a', 'a', 'b', 'b', 'b', 'b']
);

$split = new StratifiedRandomSplit($dataset, 0.5);

Split will have equal amounts of each target. Two of the target a and two of b.