train($samples, $targets); $this->assertEquals(4.03, $regression->predict([64]), '', $delta); } public function testPredictMultiFeaturesSamples(): void { $delta = 0.01; $samples = [[73676, 1996], [77006, 1998], [10565, 2000], [146088, 1995], [15000, 2001], [65940, 2000], [9300, 2000], [93739, 1996], [153260, 1994], [17764, 2002], [57000, 1998], [15000, 2000]]; $targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400]; $regression = new SVR(Kernel::LINEAR); $regression->train($samples, $targets); $this->assertEquals([4109.82, 4112.28], $regression->predict([[60000, 1996], [60000, 2000]]), '', $delta); } public function testSaveAndRestore(): void { $samples = [[60], [61], [62], [63], [65]]; $targets = [3.1, 3.6, 3.8, 4, 4.1]; $regression = new SVR(Kernel::LINEAR); $regression->train($samples, $targets); $testSamples = [64]; $predicted = $regression->predict($testSamples); $filename = 'svr-test'.rand(100, 999).'-'.uniqid(); $filepath = tempnam(sys_get_temp_dir(), $filename); $modelManager = new ModelManager(); $modelManager->saveToFile($regression, $filepath); $restoredRegression = $modelManager->restoreFromFile($filepath); $this->assertEquals($regression, $restoredRegression); $this->assertEquals($predicted, $restoredRegression->predict($testSamples)); } }