How to use skmultilearn to train models on label specific data
One-vs-Rest is the method of solving the multi-label problem you are trying to address, it is the transformation type. You just need to generate a different training set for each simple classifier so that you have all the combinations between the original attributes and each of the labels. Pandas can be useful for the manipulation of the data and the generation of the different datasets for each simple classifier. Note that using this strategy in its original form ignores the relationships between the tags.
I am using skmultilearn library to solve a multi-label machine learning problem. There are 5 labels with binary data (0 or 1). Sklearn logistic regression is being used as base classifier. But I need to set label specific features for each classifier. The label data of one classifier to be used as feature of another classifier.
I am not able to figure out on how to do that.
Any help appreciated.