Chapter 13

Getting Started with RapidMiner

Abstract

The final chapter is the kickstarter for the main tools that one would need to become familiar with in building predictive analytics models using RapidMiner. We start out by introducing the basic graphical user interface for the program and cover the basic data exploration, transformation, and preparation steps for analysis. We also cover the process of optimizing model parameters using RapidMiner’s built-in optimization tools. With this high-level overview, one can go back to any of the earlier chapters to learn about a specific technique and understand how to use RapidMiner to build models using that machine learning algorithm.

Keywords

Data exploration; data preparation; optimization; rapidMiner ...

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