def train(self, arr, remember=True,
regression_type="Ridge"):
f = Features()
if os.path.exists(self.filename):
self.clf = self._load_clf()
train_X, train_y = f.proportion_class(arr)
else:
self.clf = self.new_clf(regression_type=regression_type)
train_X, train_y = f.proportion_class(arr, len(arr))
self.clf.fit(train_X, train_y)
if remember:
self._save_clf()
return train_X, train_y
