Ejemplo n.º 1
0
    def predict(self):
        print 'Predicting'

        if self.classifier == 'knn':
            train_score = self.model.score(self.x_train, self.y_train)
            print 'KNN train score:', train_score

            if self.do_validation():
                val_score = self.model.score(self.x_validate, self.y_validate)
                print 'KNN val score: ', val_score
        else:
            import pprint

            self.predict_train = self.model.predict_proba(self.x_train)
            print 'Training Score logloss: ', functions.logloss(self.predict_train, self.y_train), ',',
            print 'Training Score precision: ', functions.precision(self.predict_train, self.y_train), ',',

            if self.do_validation():
                self.predict_validate = self.model.predict_proba(self.x_validate)
                precision = functions.logloss(self.predict_validate, self.y_validate)
                print 'Validation Score: ', precision, ',',
                precision = functions.precision(self.predict_validate, self.y_validate)
                print 'Validation Score precision: ', precision, ',',
Ejemplo n.º 2
0
def print_accuracy(predicted, y):
    print "logloss: ", functions.logloss(predicted, y)
    print "precision: ", functions.precision(predicted, y)