Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Machine Learning with R

You're reading from   Mastering Machine Learning with R Master machine learning techniques with R to deliver insights for complex projects

Arrow left icon
Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783984527
Length 400 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Cory Lesmeister Cory Lesmeister
Author Profile Icon Cory Lesmeister
Cory Lesmeister
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. A Process for Success 2. Linear Regression – The Blocking and Tackling of Machine Learning FREE CHAPTER 3. Logistic Regression and Discriminant Analysis 4. Advanced Feature Selection in Linear Models 5. More Classification Techniques – K-Nearest Neighbors and Support Vector Machines 6. Classification and Regression Trees 7. Neural Networks 8. Cluster Analysis 9. Principal Components Analysis 10. Market Basket Analysis and Recommendation Engines 11. Time Series and Causality 12. Text Mining A. R Fundamentals Index

Data understanding and preparation

Let's start with loading the R packages that we will need for this chapter. As always, make sure that you have installed them first:

> library(cluster) #conduct cluster analysis
> library(compareGroups) #build descriptive statistic tables
> library(HDclassif) #contains the dataset
> library(NbClust) #cluster validity measures
> library(sparcl) #colored dendrogram

The dataset is in the HDclassif package, which we installed. So, we can load the data and examine the structure with the str() function:

> data(wine)

> str(wine)
'data.frame':178 obs. of  14 variables:
 $ class: int  1 1 1 1 1 1 1 1 1 1 ...
 $ V1   : num  14.2 13.2 13.2 14.4 13.2 ...
 $ V2   : num  1.71 1.78 2.36 1.95 2.59 1.76 1.87 2.15 1.64 1.35 ...
 $ V3   : num  2.43 2.14 2.67 2.5 2.87 2.45 2.45 2.61 2.17 2.27 ...
 $ V4   : num  15.6 11.2 18.6 16.8 21 15.2 14.6 17.6 14 16 ...
 $ V5   : int  127 100 101 113 118 112 96 121 97 98 ...
 $ V6   : num  2.8 2.65...
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