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)