public function predict($x, $threshold = 0.5)
{
$prob = $this->sigmoid(parent::predict($x));
if ($threshold === null) {
return $prob;
}
return $prob > $threshold;
}
public function testPredict()
{
$xs = array(array(1, 2, 2, 2), array(1, 3, 3, 3), array(1, 4, 4, 4), array(1, 5, 5, 5));
$ys = array(6, 9, 12, 15);
$parameters = array(0, 0, 0, 0);
$gd = new LL_GradientDescent_Regression($xs, $ys, $parameters);
$gd->setLearningRate(0.01);
$gd->setRepetitions(10000);
$gd->train();
$results = $gd->getParameters();
$estimates = array();
foreach ($xs as $index => $x_row) {
$estimates[$index] = 0;
foreach ($x_row as $paramIndex => $xi) {
$estimates[$index] += $results[$paramIndex] * $xi;
}
}
// manually computed estimates.
foreach ($estimates as $index => $est) {
$this->assertEquals($gd->predict($xs[$index]), $est);
}
}
