b115f1f721594772ca12e02dc388b1b210a2ee73,experiments/mnist.py,,,#,31

Before Change

    (x_train, y_train), (x_test, y_test) = mnist.load_data()
    X = np.concatenate((x_train, x_test))
    Y = np.concatenate((y_train, y_test))
    clf = ImageClassifier(searcher_type=sys.argv[1], path=sys.argv[2], verbose=False)
    clf.fit(x_train, y_train)
    y = clf.evaluate(x_test, y_test)
    print(y)
    // MLP for Pima Indians Dataset with 10-fold cross validation
    // scores = clf.cross_validate(X, Y, 2)

After Change

    x_test = x_test.reshape(x_test.shape + (1,))
    X = np.concatenate((x_train, x_test))
    Y = np.concatenate((y_train, y_test))
    clf = ImageClassifier(searcher_type="bayesian", path="~/temp_models", verbose=True)

    clf.fit(x_train, y_train, time_limit=12*60*60)
    // clf.final_fit(x_train, y_train)
    y = clf.evaluate(x_test, y_test)
    print(y)
    // MLP for Pima Indians Dataset with 10-fold cross validation
    scores = clf.cross_validate(X, Y, 10)
    print(scores)
    print(np.mean(scores))
    print(np.std(scores))

    // split into input (X) and output (Y) variables
    // define 10-fold cross validation test harness

Instances