45 lines
1.1 KiB
Markdown
45 lines
1.1 KiB
Markdown
# Stratified Random Split
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Analogously to `RandomSpilt` class, samples are split to two groups: train group and test group.
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Distribution of samples takes into account their targets and trying to divide them equally.
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You can adjust the number of samples in each group.
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### Constructor Parameters
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* $dataset - object that implements `Dataset` interface
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* $testSize - a fraction of test split (float, from 0 to 1, default: 0.3)
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* $seed - seed for random generator (e.g. for tests)
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```
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$split = new StratifiedRandomSplit($dataset, 0.2);
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```
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### Samples and labels groups
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To get samples or labels from test and train group, you can use getters:
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```
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$dataset = new StratifiedRandomSplit($dataset, 0.3, 1234);
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// train group
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$dataset->getTrainSamples();
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$dataset->getTrainLabels();
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// test group
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$dataset->getTestSamples();
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$dataset->getTestLabels();
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```
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### Example
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```
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$dataset = new ArrayDataset(
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$samples = [[1], [2], [3], [4], [5], [6], [7], [8]],
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$targets = ['a', 'a', 'a', 'a', 'b', 'b', 'b', 'b']
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);
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$split = new StratifiedRandomSplit($dataset, 0.5);
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```
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Split will have equal amounts of each target. Two of the target `a` and two of `b`.
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