后者，predict_proba 是一种(软)分类器的方法，输出实例在每个类中的概率.

The latter, predict_proba is a method of a (soft) classifier outputting the probability of the instance being in each of the classes.

前者，decision_function，找到到分离超平面的距离.例如，a(n) SVM 分类器找到将空间分成与分类结果相关联的区域的超平面.这个函数，给定一个点，找到到分隔符的距离.

The former, decision_function, finds the distance to the separating hyperplane. For example, a(n) SVM classifier finds hyperplanes separating the space into areas associated with classification outcomes. This function, given a point, finds the distance to the separators.

我猜想 predict_prob 对您的情况更有用，一般来说 - 另一种方法更特定于算法.

I'd guess that predict_prob is more useful in your case, in general - the other method is more specific to the algorithm.