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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

Product type Paperback

Published in May 2019

Publisher

ISBN-13 9781838556334

Length 502 pages

Edition 1st Edition

Languages

R

Concepts

Machine Learning

Authors (2):

Jojo Moolayil

Karthik Ramasubramanian

View More author details

Table of Contents (12) Chapters

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

Highly Correlated Variables

Generally, two highly correlated variables likely contribute to the prediction ability of the model, which makes one redundant. For example, if we have a dataset with age, height, and BMI as variables, we know that BMI is a function of age and height and it will always be highly correlated with the other two. If it's not, then something is wrong with the BMI calculation. In such cases, one might decide to remove the other two. However, it is always not this straight. In certain cases, a pair of variables might be highly correlated, but it is not easy to interpret why that is the case. In such cases, one can randomly drop one of the two.

Exercise 82: Plotting a Correlated Matrix

In this exercise, we will compute the correlation between a pair of variables and draw a correlation plot using the corrplot package.

Perform the following steps to complete the exercise:

Import the required libraries using the following command:
```
library(mlbench)
library(caret)
```
The output is...

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Authors (2)

Karthik Ramasubramanian

Karthik Ramasubramanian

Karthik Ramasubramanian completed his M.Sc. in Theoretical Computer Science at PSG College of Technology, India, where he pioneered the application of machine learning, data mining, and fuzzy logic in his research work on computer and network security. He has over seven years' experience of leading data science and business analytics in retail, Fast-Moving Consumer Goods, e-commerce, information technology, and the hospitality industry for multinational companies and unicorn start-ups. He is a researcher and a problem solver with diverse experience of the data science life cycle, starting from data problem discovery to creating data science proof of concepts and products for various industry use cases. In his leadership roles, Karthik has been instrumental in solving many ROI-driven business problems via data science solutions. He has mentored and trained hundreds of professionals and students globally in data science through various online platforms and university engagement programs. He has also developed intelligent chatbots based on deep learning models that understand human-like interactions, customer segmentation models, recommendation systems, and many natural language processing models. He is an author of the book Machine Learning Using R, published by Apress, a publishing house of Springer Business+Science Media. The book was a big success with more than 50,000 online downloads and hardcover sales. The book was subsequently published as a second edition with extended chapters on Deep Learning and Time Series Modeling.

See other products by Karthik Ramasubramanian

Jojo Moolayil

Jojo Moolayil

Jojo Moolayil is an artiﬁcial intelligence, deep learning, machine learning, and decision science professional with over six years of industrial experience. He is the author of Learn Keras for Deep Neural Networks, published by Apress, and Smarter Decisions – The Intersection of IoT and Decision Science, published by Packt Publishing. He has worked with several industry leaders on high-impact, critical data science and machine learning projects across multiple verticals. He is currently associated with Amazon Web Services as a research scientist in Canada. Apart from writing books on AI, decision science, and the internet of things, Jojo has been a technical reviewer for various books in the same ﬁelds published by Apress and Packt Publishing.

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