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When building a decision tree, we want to split the nodes in a way that decreases entropy and increases information gain.

Here you will find the answers of “When building a decision tree, we want to split the nodes in a way that decreases entropy and increases information gain.“. This question is a part ” Machine Learning With R

Question: When building a decision tree, we want to split the nodes in a way that decreases entropy and increases information gain.

  1. True
  2. False

Correct Answer: 1

About Machine Learning With R

This Machine Learning with R course dives into the basics of machine learning using an approachable, and well-known, programming language. You’ll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.

Look at real-life examples of Machine learning and how it affects society in ways you may not have guessed!

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