RapidMiner is one of the finest tools for building machine learning models, including deep learning models. According to a KDnuggets 2018 poll, RapidMiner stands at second place, beating R, Excel, and many other known software packages in frequency of use in real projects.

In this guide, you will learn how to build your first regression and classification model using RapidMiner.

Setting Up the Data

To start, download the House Prices: Advanced Regression Techniques training dataset from Kaggle. The dataset has 81 attributes and 1460 records. To focus on machine learning and not data cleaning, create a dataset consisting of only five attributes: OverallQual, LotArea, Street, GarageArea, and SalePrice . These five attributes will be used in building both regression and classification models.

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