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 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 equals amount of each target. Two of the target a and two of b.