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Practical Machine Learning with R

You're reading from   Practical Machine Learning with R Define, build, and evaluate machine learning models for real-world applications

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781838550134
Length 416 pages
Edition 1st Edition
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Authors (3):
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 Jeyaraman Jeyaraman
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Jeyaraman
 Olsen Olsen
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Olsen
 Wambugu Wambugu
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Wambugu
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Toc

Table of Contents (8) Chapters Close

About the Book 1. An Introduction to Machine Learning FREE CHAPTER 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

Identifying the Category of Prediction

Based on the category of prediction, we will perform different pre-processing steps. The category of prediction could be any of these:

  • Categorical Prediction: In this type of prediction, the output to be predicted will have class values such as yes, no, or given categories.
  • Numeric Prediction: In a numeric prediction, the output that will be predicted is a numeric value, such as predicting the cost of a house.
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