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Practical Machine Learning with R

You're reading from  Practical Machine Learning with R

Product type Book
Published in Aug 2019
Publisher Packt
ISBN-13 9781838550134
Pages 416 pages
Edition 1st Edition
Languages
Authors (3):
Brindha Priyadarshini Jeyaraman Brindha Priyadarshini Jeyaraman
Profile icon Brindha Priyadarshini Jeyaraman
Ludvig Renbo Olsen Ludvig Renbo Olsen
Profile icon Ludvig Renbo Olsen
Monicah Wambugu Monicah Wambugu
Profile icon Monicah Wambugu
View More author details
Toc

Table of Contents (8) Chapters close

About the Book 1. An Introduction to Machine Learning 2. Data Cleaning and Pre-processing 3. Feature Engineering 4. Introduction to neuralnet and Evaluation Methods 5. Linear and Logistic Regression Models 6. Unsupervised Learning 1. Appendix

Handling Categorical Variables

Categorical variables are a list of string values or numeric values for an attribute. For instance, gender can be "Male" or "Female". There are two types of categories: nominal and ordinal. In nominal categorical data, there is no ordering among the values in that attribute. This is the case with gender values. Ordinal categories have some order within the set of values. For instance, for temperature "Low," "Medium," and "High" have an order.

  • Label Encoding: String literals needs to be converted to numeric values, where "Male" can take value 1 and "Female" can take value 2. This is called integer encoding or label encoding. The integer values have a natural ordering so this may be suitable in cases dealing with categorical data, which is ordinal.
  • One-Hot Encoding: For nominal categories, label encoding is not suitable as the natural order of the numbers may be learned by the machine...
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