def train_test_combined(features_labels, fractions, train, test, mode):
features_labels = np.array(features_labels, dtype=object)
reg = Combined(random_state=1, mode=mode, n_jobs=N_JOBS)
reg.fit(features_labels[train], fractions[train])
rs = []
for fs, frac in zip(features_labels[test], fractions[test]):
fs = [f for f, _ in fs]
r = reg.predict(fs, clip01=False)
rs.append(r)
return np.array(rs)
def train_test_combined(features_labels, fractions, train, test, mode):
features_labels = np.array(features_labels, dtype=object)
reg = Combined(random_state=1, mode=mode, n_jobs=N_JOBS)
reg.fit(features_labels[train], fractions[train])
rs = []
for fs,frac in zip(features_labels[test], fractions[test]):
fs = [f for f,_ in fs]
r = reg.predict(fs, clip01=False)
rs.append(r)
return np.array(rs)
