def test_BaseLearningSpec_can_be_used_for_training(self):
train = 'train --cv=2'
self.assertEqual(None, utils.run_mlpal(train, self.SETUP), "make train is failing")
def test_BaseLearningSpec_can_be_used_for_searching(self):
search = 'search --cv=2'
self.assertEqual(None, utils.run_mlpal(search, self.SETUP), "make search is failing")
def test_benchmark_is_ok(self):
self.assertEqual(None, utils.run_mlpal('train'), "train is failing")
self.assertEqual(None, utils.run_mlpal('benchmark --clfpath=dumps/last.dump'), "benchmark is failing")
def test_train_is_ok(self):
self.assertEqual(None, utils.run_mlpal('train'), "train is failing")
def test_learning_curves_is_ok(self):
self.assertEqual(None, utils.run_mlpal('learning_curves -n=100 --cv=2 --points=2'), "learning_curves is failing")
def test_plot_pca_is_ok(self):
self.assertEqual(None, utils.run_mlpal('plot_pca'), "plot_pca is failing")
def test_search_is_ok(self):
self.assertEqual(None, utils.run_mlpal('search --cv=3 -j 2 --random-state=42'), "search is failing")
def test_misclassified_task_is_ok(self):
self.assertEqual(None, run_mlpal('misclassified -f --cv=2'), "misclassified task with force is failing")
self.assertEqual(None, run_mlpal('misclassified --cv=2'), "misclassified task without force is failing")
def test_plot_pca_is_ok(self):
self.assertEqual(None, utils.run_mlpal('plot_pca'), "plot_pca is failing")
self.assertEqual(None, utils.run_mlpal('plot_pca', setup='mlpal.tests.dummy_setup_with_pipeline'), "plot_pca is failing")
