import pandas as pd
import numpy as np
#from sknn.mlp import Classifier, Layer
from sklearn.neural_network import MLPClassifier
from sklearn.cross_validation import cross_val_score
from sklearn.svm import LinearSVC
from sklearn.decomposition import PCA

train = pd.read_csv("../input/train.csv")


x_tr = train.values[:, 1:].astype(float)/255
y_tr = train.values[:, 0]


n_trees = 80
recognizer = PCA(n_components=100)
x_red = recognizer.fit_transform(x_tr)
#print(x_tr.shape)
#print(x_red.shape)
recognizer = LinearSVC()

#cross validation score
score = cross_val_score(recognizer, x_red, y_tr)
score = np.mean(score)
print(score)

#in-sample score
recognizer.fit(x_red, y_tr)
print(recognizer.score(x_red, y_tr))