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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

Product type Paperback

Published in Jun 2017

Publisher Packt

ISBN-13 9781785886188

Length 576 pages

Edition 1st Edition

Languages

R

Tools

Splunk

Concepts

Predictive Analytics

Author (1):

Ralph Winters

View More author details

Table of Contents (13) Chapters

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

Summarizing the metrics

Running a summary on the rules_clust object indicates an average support of 0.05, and average confidence of 0.43.

This demonstrates that using clustering can be a viable way to develop association rules, and reduce resources and the number of dimensions at the same time:

    support          confidence           lift     
 Min.   :0.02044   Min.   :0.09985   Min.   :0.989 
 1st Qu.:0.02664   1st Qu.:0.19816   1st Qu.:1.006 
 Median :0.03066   Median :0.27143   Median :1.526 
 Mean   :0.05040   Mean   :0.43040   Mean   :1.608 
 3rd Qu.:0.04234   3rd Qu.:0.81954   3rd Qu.:1.891 
 Max.   :0.17080   Max.   :1.00000   Max.   :3.022

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Authors (1)

Winters

Winters

Ralph Winters started his career as a database researcher for a music performing rights organization (he composed as well!), and then branched out into healthcare survey research, finally landing in the Analytics and Information technology world. He has provided his statistical and analytics expertise to many large fortune 500 companies in the financial, direct marketing, insurance, healthcare, and pharmaceutical industries. He has worked on many diverse types of predictive analytics projects involving customerretention, anti-money laundering, voice of the customer text mining analytics, and health care risk and customer choice models. He is currently data architect for a healthcare services company working in the data and advanced analytics group. He enjoys working collaboratively with a smart team of business analysts, technologists, actuaries as well as with other data scientists. Ralph considered himself a practical person. In addition to authoring Practical Predictive Analytics for Packt Publishing, he has also contributed two tutorials illustrating the use of predictive analytics in Medicine and Healthcare in Practical Predictive Analytics and Decisioning Systems for Medicine: Miner et al., Elsevier September, 2014, and also presented Practical Text Mining with SQL using Relational Databases, at the 2013 11th Annual Text and Social Analytics Summit in Cambridge, MA. Ralph resides in New Jersey with his loving wife Katherine, amazing daughters Claire and Anna, and his four-legged friends, Bubba and Phoebe, who can be unpredictable. Ralph's web site can be found at ralphwinters.com

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