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Practical Predictive Analytics

You're reading from  Practical Predictive Analytics

Product type Book
Published in Jun 2017
Publisher Packt
ISBN-13 9781785886188
Pages 576 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Ralph Winters Ralph Winters
Profile icon Ralph Winters
LinkedIn
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
See other products by Ralph Winters

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 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

The forecast (fit) method

The forecast method contains many objects that you can display, such as the fitted value, original values, confidence intervals, and residuals. Use str(forecast(fit)) to see which objects are available.

We will use cbind to print out the original data point, fitted data point, and model fitting method.

cbind(forecast(fit)$method,forecast(fit)$x,forecast(fit)$fitted,forecast(fit)$residuals) 
Time Series: 
Start = 1999  
End = 2012  
Frequency = 1  
     forecast(fit)$method   forecast(fit)$x forecast(fit)$fitted forecast(fit)$residuals 
1999           ETS(A,N,N)  0.15412470117969    0.154120663632029    4.03754766081788e-06 
2000           ETS(A,N,N) 0.157413125646824    0.154124700770241     0.00328842487658335 
2001           ETS(A,N,N) 0.162942355969924    0.157412792166205     0.00552956380371911 
2002           ETS(A,N,N) 0.160986044554207    0.162941795214416      -0.001955750660209 
2003           ETS(A,N,N) 0.148533847659868    0.160986242887746     -0.0124523952278778...
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Authors (1)

Profile icon Ralph Winters
LinkedIn
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
Read more
See other products by Ralph Winters

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