Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Applied Supervised Learning with R

You're reading from   Applied Supervised Learning with R Use machine learning libraries of R to build models that solve business problems and predict future trends

Arrow left icon
Product type Paperback
Published in May 2019
Publisher
ISBN-13 9781838556334
Length 502 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Jojo Moolayil Jojo Moolayil
Author Profile Icon Jojo Moolayil
Jojo Moolayil
Karthik Ramasubramanian Karthik Ramasubramanian
Author Profile Icon Karthik Ramasubramanian
Karthik Ramasubramanian
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Applied Supervised Learning with R
Preface
1. R for Advanced Analytics FREE CHAPTER 2. Exploratory Analysis of Data 3. Introduction to Supervised Learning 4. Regression 5. Classification 6. Feature Selection and Dimensionality Reduction 7. Model Improvements 8. Model Deployment 9. Capstone Project - Based on Research Papers Appendix

Decision Trees


Like logistic regression, there is another popular classification technique that is very popular due to its simplicity and white-box nature. A decision tree is a simple flowchart that is represented in the form of a tree (an inverted tree). It starts with a root node and branches into several nodes, which can be traversed based on a decision, and ends with a leaf node where the final outcome is determined. Decision trees can be used for regression, as well as classification use cases. There are several variations of decision trees implemented in machine learning. A few popular choices are listed here:

  • Iterative Dichotomiser 3 (ID3)

  • Successor to ID3 (C4.5)

  • Classification and Regression Tree (CART)

  • CHi-squared Automatic Interaction Detector (CHAID)

  • Conditional Inference Trees (C Trees)

The preceding list is not exhaustive. There are other alternatives, and each of them has small variations in how they approach the tree creation process. In this chapter, we will limit our exploration...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image