Classifying multilabeled data points using Mulan

So far, we have seen multiclass classification that aims to classify a data instance into one of several classes. Multilabeled data instances are data instances that can have multiple classes or labels. The machine learning tools that we have used so far are not capable of handling data points that have this characteristic of having multiple target classes.

For classifying multilabeled data points, we will be using an open source Java library named Mulan. Mulan has implementations of various classification, ranking, feature selection, and evaluation of models. As Mulan does not have GUI, the only way to use it is either by command line or using its API. In this recipe, we will limit our focus on ...

Get Java Data Science Cookbook now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.