def run_train():
# t0 = time.time()
pt = Preprocessor()
tr = Trainer_nn()
X_train, y_train = pt.get_data_labels()
X_test, y_test = pt.get_data_labels("test")
# X_train, y_train = pt.load_data()
# X_test, y_test = pt.load_data("mnist_test_data.npz")
clf = tr.mlp(X_train, y_train)
tr.save_model(clf, "mlp_mnist_Hu300x300ReluSgdIter100Acc96Sample60000.m")
tester = Tester("mlp_mnist_Hu300x300ReluSgdIter100Acc96Sample60000.m")
mt, score, repo = tester.clf_quality(X_test, y_test)
print(mt, score, repo)
return clf
def run_train():
t0 = time.time()
pt = Preprocessor()
tr = Trainer()
X_train, y_train = pt.get_data_labels()
X_test, y_test = pt.get_data_labels("test")
t1 = time.time()
print(t1 - t0)
clf = tr.svc(X_train, y_train)
print(time.time() - t1)
tr.save_model(clf, "mnist_svm.m")
tester = Tester("mnist_svm.m")
mt, score, repo = tester.clf_quality(X_test, y_test)
print(mt, score, repo)
return clf