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Practical Predictive Analytics

You're reading from   Practical Predictive Analytics Analyse current and historical data to predict future trends using R, Spark, and more

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781785886188
Length 576 pages
Edition 1st Edition
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Author (1):
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Ralph Winters Ralph Winters
Author Profile Icon Ralph Winters
Ralph Winters
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Predictive Analytics FREE CHAPTER 2. The Modeling Process 3. Inputting and Exploring Data 4. Introduction to Regression Algorithms 5. Introduction to Decision Trees, Clustering, and SVM 6. Using Survival Analysis to Predict and Analyze Customer Churn 7. Using Market Basket Analysis as a Recommender Engine 8. Exploring Health Care Enrollment Data as a Time Series 9. Introduction to Spark Using R 10. Exploring Large Datasets Using Spark 11. Spark Machine Learning - Regression and Cluster Models 12. Spark Models – Rule-Based Learning

Compressing descriptions using camelcase


For long descriptions, sometimes it is beneficial to compress them into camelcase to improve readability. This is especially valuable when viewing descriptions that are labels on x or y axes.

Camelcase is a method that some programmers use for writing compound words, where spaces are first removed, and then each word begins with a capital letter. It is also a way of conserving space.

To accomplish this, we can write a function called .simpleCap, which performs this function. To illustrate how it works, we will pass it a two element character vector c("A certain good book","A very easy book"), and observe the results.

Custom function to map to camelcase

This is a simple example use of this function that maps the two character vector c("A certain good book", "A very easy book") to camelcase. This vector is mapped to two new elements:

[1] "ACertainGoodBook", and  [2] "AVeryEasyBook" 
 
# change descriptions to camelcase maybe append to itemnumber for uniqueness...
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