是否有可能获得通过火花mllib GradientBoostedTrees类的概率？ [英] Is it possible to obtain class probabilities using GradientBoostedTrees with spark mllib?

问题描述

我目前正在与火花mllib工作。

I am currently working with spark mllib.

我已经创建使用渐变Boosting算法与类GradientBoostedTrees文本分类：

I have created a text classifier using the Gradient Boosting algorithm with the class GradientBoostedTrees:

梯度提振树

目前我得到predictions知道班级的新元素，但我想（硬判决前的输出值）来获得类的概率。

Currently I obtain the predictions to know the class of new elements but I would like to obtain the class probabilities (the value of the output before the hard decision).

在其他mllib算法，如回归，你可以从分类删除的门槛来获得类的概率，但我不能找到一种方法，做GradientBosstedTrees相同的过程。

In other mllib algorithms like logistic regression you can remove the threshold from the classifier to obtain the class probabilities but I can not find a way to do the same procedure with GradientBosstedTrees.

推荐答案

据我所知，目前还无法但也可以用随机森林。

As far as I know, it's not currently possible but it is possible with random forest.

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