y_pred = self.predict(X)
self.scores = precision_recall_fscore_support(y, y_pred)
self.support = dict(zip(self.classes_, self.scores[-1]))
return self.draw()
def draw(self):
Renders the class balance chart across the axis.
After Change
self.scores = precision_recall_fscore_support(y, y_pred)
self.support = dict(zip(self.classes_, self.scores[-1]))
self.draw()
// Retrieve and store the score attribute from the sklearn classifier
self.score_ = self.estimator.score(X, y)return self.score_
def draw(self):
Renders the class balance chart across the axis.