Book Image

Java Data Science Cookbook

By : Rushdi Shams
Book Image

Java Data Science Cookbook

By: Rushdi Shams

Overview of this book

If you are looking to build data science models that are good for production, Java has come to the rescue. With the aid of strong libraries such as MLlib, Weka, DL4j, and more, you can efficiently perform all the data science tasks you need to. This unique book provides modern recipes to solve your common and not-so-common data science-related problems. We start with recipes to help you obtain, clean, index, and search data. Then you will learn a variety of techniques to analyze, learn from, and retrieve information from data. You will also understand how to handle big data, learn deeply from data, and visualize data. Finally, you will work through unique recipes that solve your problems while taking data science to production, writing distributed data science applications, and much more - things that will come in handy at work.
Table of Contents (16 chapters)
Java Data Science Cookbook
About the Author
About the Reviewer
Customer Feedback

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 classification and evaluation of classification of a multilabeled dataset using two different classifiers.

Getting ready

In order to perform this recipe, we will require the following:

  1. First, download Mulan. In our recipe, we will be using its version...