gistfile1.txt

from sklearn.ensemble import RandomForestClassifier, VotingClassifier

from mlxtend.feature_selection import ColumnSelector
from sklearn.pipeline import make_pipeline


y = df1.index
x = preprocessing.scale(df1)

pipe_phy = make_pipeline(ColumnSelector(cols=('A', 'B', 'C')), SVM)
pipe_phy = make_pipeline(ColumnSelector(cols=('D', 'E', 'F')), SVM)


ens = VotingClassifier(estimators=[pipe_phy, pipe_fa])

cv = KFold(n_splits=10, random_state=None, shuffle=True)
for train_index, test_index in cv.split(x):
    x_train, x_test = x[train_index], x[test_index]
    y_train, y_test = y[train_index], y[test_index]
    ens.fit(x_train,y_train)
    print(ens.score(x_test, y_test))