04573605a3bef45d29d81302bce154f220bbd7f5,finetune/target_encoders.py,OrdinalRegressionEncoder,rank_to_thresholds,#OrdinalRegressionEncoder#Any#,125

Before Change

        //print("RANK: {}".format(x[0]))
        for i in range(len(x)):
            rank = int(x[i])
            thresholds.append(np.concatenate((np.ones(rank,),np.zeros((num_thresholds-rank),))))
        return thresholds

    def inverse_transform(self, y):

After Change

        x = x[:10000]
        num_thresholds = len(self.categories_[0])-1
        thresholds = [np.concatenate((np.ones(int(rank)),np.zeros((num_thresholds-int(rank))))) for rank in x]
        return np.array(thresholds)

    def inverse_transform(self, y):
        //this commented part doesn"t work yet
        //y = np.asarray(y)

Instances