import sklearn.cross_validation as cv # définition d'un objet Validation Croisée: cvk = cv.StratifiedKFold(Y, n_folds=5) # 5 sous-ensembles de données classifier = lin.LogisticRegression(); k=0 for train_index, test_index in cvk: # parcours des 5 sous-ensembles classifier.fit(X[train_index],Y[train_index]) ypredL = classifier.predict(X[train_index]) ypredT = classifier.predict(X[test_index]) print "(RL) iteration ",k," pc good (Learn) ",np.where(ypredL == Y[train_index],1.,0.).sum()/len(train_index) print "(RL) iteration ",k," pc good (Test) ",np.where(ypredT == Y[test_index],1.,0.).sum()/len(test_index) k+=1