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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):

Winters

View More author details

Table of Contents (19) Chapters

Title Page

Credits

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Getting Started with Predictive Analytics

2. The Modeling Process FREE CHAPTER

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

Summary

In this chapter, we learned about the various structured approaches to predictive analytics and how implementing an analytics project in a methodical way can enhance the success of an analytics project through collaboration and communication. We went through the various steps of the CRISP-DM methodology and demonstrated tools that you could use to help you progress along these steps.

We discussed the benefits of sampling and how it could speed up your project. SQL was demonstrated to illustrate basic charts and plots, so that you can begin to develop insight even before you create a first model. We showed that data simulation could also be used at the data understanding phase as a preliminary modeling tool to do "what ifing", even before actual company data is obtained.

We learned about the various types of data that you will encounter, and showed some examples of independent and dependent variables and the importance of doing preliminary 1-way and 2-way variable analysis as a precursor...

You have been reading a chapter from

Practical Predictive Analytics

Published in: Jun 2017

Publisher: Packt

ISBN-13: 9781785886188

© 2017 Packt Publishing Limited All Rights Reserved

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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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