import logging

try:
    from sklearn.model_selection import train_test_split
except ImportError:
    from sklearn.cross_validation import train_test_split
from sklearn.datasets import make_classification

from mla.metrics.metrics import accuracy
from mla.svm.kernerls import Linear, RBF
from mla.svm.svm import SVM

logging.basicConfig(level=logging.DEBUG)


def classification():
    # Generate a random binary classification problem.
    X, y = make_classification(
        n_samples=1200,
        n_features=10,
        n_informative=5,
        random_state=1111,
        n_classes=2,
        class_sep=1.75,
    )
    # Convert y to {-1, 1}
    y = (y * 2) - 1
    X_train, X_test, y_train, y_test = train_test_split(
        X, y, test_size=0.2, random_state=1111
    )

    for kernel in [RBF(gamma=0.1), Linear()]:
        model = SVM(max_iter=500, kernel=kernel, C=0.6)
        model.fit(X_train, y_train)
        predictions = model.predict(X_test)
        print(
            "Classification accuracy (%s): %s" % (kernel, accuracy(y_test, predictions))
        )


if __name__ == "__main__":
    classification()
