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_