from sklearn.neural_network import MLPClassifier
import csv
import numpy as np





def read_data(path):
    X = []
    with open(path, 'rb') as csvfile:
        spamreader = csv.reader(csvfile, delimiter=',', quotechar='|')
        X.append(list(spamreader))
    return np.array(X[0]).astype(np.float)


X = read_data('inputData.csv')
Y = read_data('answerData.csv')
Test = read_data('testData.csv')
print X.shape
print Test.shape
Y = Y.flatten()
nn = MLPClassifier(alpha=0.001, hidden_layer_sizes=(200,))

nn.fit(X, Y)

score = nn.score(X, Y)

print score