def handcrafted(): dataset = data.load_eviction(dataset_type='handcrafted') fname = '%s/results_HANDCRAFTED_dataset_OVER.csv' % DIR test_runner.predict(MODELS, dataset, fname, N_TESTS, OVERSAMPLE)
def pca(): dataset = data.load_eviction(dataset_type='pca') fname = '%s/results_PCA_dataset_OVER.csv' % DIR test_runner.predict(MODELS, dataset, fname, N_TESTS, OVERSAMPLE)
def rlogistic(): dataset = data.load_eviction(dataset_type='rlogistic') fname = '%s/results_RLOGISTIC_dataset_OVER.csv' % DIR test_runner.predict(MODELS, dataset, fname, N_TESTS, OVERSAMPLE)
def full(): dataset = data.load_eviction() fname = '%s/results_FULL_dataset_OVER.csv' % DIR test_runner.predict(MODELS, dataset, fname, N_TESTS, OVERSAMPLE)