Practicing Machine Learning Techniques in R with MLR Package

Introduction In R, we often use multiple packages for doing various machine learning tasks. For example: we impute missing value using one package, then build a model with another and finally evaluate their performance using a third package. The problem is, every package has a set of specific parameters. While working with many packages, we end up spending a lot of time to figure out which parameters are important. Don’t you think? To solve this problem, I researched and came across a R package named MLR, which is absolutely incredible at performing machine learning tasks. This package includes all of the ML algorithms which we use frequently.  In this tutorial, I’ve taken up a classification problem and tried improving its accuracy using machine learning. I haven’t explained the ML algorithms (theoretically) but focus is kept on their implementation.…

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