public function testPartitions()
{
// Arrange
$data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
$labels = [false, false, true, false, false, true, false, false, true, true];
$set = new DataSet($data, $labels);
$numberOfPartitions = 5;
$expectedTestData = [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]];
$expectedTrainingData = [[3, 4, 5, 6, 7, 8, 9, 10], [1, 2, 5, 6, 7, 8, 9, 10], [1, 2, 3, 4, 7, 8, 9, 10], [1, 2, 3, 4, 5, 6, 9, 10], [1, 2, 3, 4, 5, 6, 7, 8]];
$expectedTestLabels = [[false, false], [true, false], [false, true], [false, false], [true, true]];
$expectedTrainingLabels = [[true, false, false, true, false, false, true, true], [false, false, false, true, false, false, true, true], [false, false, true, false, false, false, true, true], [false, false, true, false, false, true, true, true], [false, false, true, false, false, true, false, false]];
// Act
// false means no shuffling
$partitioner = new CrossValidationRandomPartitioner($set, $numberOfPartitions, false);
// Assert
for ($i = 0; $i < $numberOfPartitions; $i++) {
$currentPartition = $partitioner->getPartition($i);
$currentTest = $currentPartition->getTestData();
$currentTraining = $currentPartition->getTrainingData();
$this->assertEquals($expectedTestData[$i], $currentTest->getData());
$this->assertEquals($expectedTestLabels[$i], $currentTest->getLabels());
$this->assertEquals($expectedTrainingData[$i], $currentTraining->getData());
$this->assertEquals($expectedTrainingLabels[$i], $currentTraining->getLabels());
}
}
public function run(array $dataSet, array $dataSetLabels)
{
// Generate folds
$partitioner = new CrossValidationRandomPartitioner(new DataSet($dataSet, $dataSetLabels), $this->numberOfPartitions);
$resultsList = [];
for ($i = 0; $i < $this->numberOfPartitions; $i++) {
// For each fold, train and classify
$currentPartition = $partitioner->getPartition($i);
$currentTest = $currentPartition->getTestData();
$currentTraining = $currentPartition->getTrainingData();
$classifier = new $this->classifierClassName($currentTraining->getData(), $currentTraining->getLabels());
$predicted = $this->classify($classifier, $currentTest->getData());
$resultsList[] = new RunnerResults($predicted, $currentTest->getLabels(), $currentTest->getData());
}
return RunnerResults::combine($resultsList);
}
