import time
import pandas as pd
from sklearn.decomposition import PCA
from sklearn import svm

# The competition datafiles are in the directory ../input
# Read competition data files:
start = time.time()
train = pd.read_csv("../input/train.csv")
test  = pd.read_csv("../input/test.csv")
end = time.time()
print ("finish data get, use "+str(end-start)+"s")

train_x = train.values[:,1:]
train_y = train.ix[:,0]
test_x = test.values

start = time.time()
pca = PCA(n_components=0.8,whiten=True)
train_x = pca.fit_transform(train_x)
test_x = pca.transform(test_x)
print(len(train_x[0]))
end = time.time()
print ("finish data PCA, use "+str(end-start)+"s")

start = time.time()
svc = svm.SVC(kernel='rbf',C=10)
svc.fit(train_x, train_y)
end = time.time()
print ("finish SVM train, use "+str(end-start)+"s")

start = time.time()
test_y = svc.predict(test_x)
end = time.time()
print ("finish SVM predict, use "+str(end-start)+"s")
pd.DataFrame({"ImageId": range(1,len(test_y)+1), "Label": test_y}).to_csv('out.csv', index=False, header=True)