features_test.append( features[jj] )
labels_test.append( labels[jj] )
from sklearn import model_selection
from sklearn.metrics import accuracy_score
from sklearn.naive_bayes import GaussianNB
clf = GaussianNB()
clf.fit(features_train,labels_train)
pred=clf.predict(features_test)
print accuracy_score(pred,labels_test)
from sklearn.cluster import KMeans
clf=KMeans(n_clusters=2,n_init=10)
pred=clf.fit_predict(features_test)
print accuracy_score(pred,labels_test)
from sklearn.svm import SVC
clf=SVC()
clf.fit(features_train,labels_train)
pred=clf.predict(features_test)
print accuracy_score(pred,labels_test)
'''
from sklearn import linear_model
clf=linear_model.Lasso()
clf.fit(features_train,labels_train)
pred=clf.predict(features_test)
print accuracy_score(pred,labels_test)
print clf.coef_
