Sklearn - predict_proba equivalents
So some of the models in Sci-kit learn such as Logistic Regression support the predict_proba method which I use heavily. Is there an other way for models such as Lasso to output a similar probability array, since they don't support predict_proba?
Also: I'm working with a three outcome dataset where the probabilities between the outcomes can be relatively even - any general suggestions for models/tunings to try to improve probability precision, that can handle 50+ feature columns? =)
Thanks!作者: Daniel Slätt 的来源 发布者: 2017 年 12 月 27 日
Sklearn introduced Probability calibration exactly for this purpose. Improving or adding support for classifiers without a natural probability-output.
There is also a blog-post about this.
Usage will be based on CalibratedClassifierCV.
Of those two methods, sigmoid and isotonic, the former is quite popular as the underlying method behind libsvm's probability-output, which you can see in sklearn's wrapper SVC作者: sascha 发布者: 27.12.2017 05:14