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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

Advantages of a structured approach


Analytic projects have many components. That is where a structured methodology can help. Many benefits can be gained if there is a structure which is placed upon discovery and analysis, rather than only on pure model building. The discovery and insight gained will certainly be utilized past the original intent of the problem.

We assume that the quick-thinking "hare brain" will beat out the slower Intuition of the "tortoise mind." However, now research in cognitive science is changing this understanding of the human mind. It suggests that patience and confusion--rather than rigor and certainty--are the essential precursors of wisdom.

-Guy Claxton

Ways in which structured methodologies can help

Here are several points to bear in mind concerning the advantages of structured methodologies:

  • Data is coming at us fast and furious. We need to keep track of the many data sources, evaluate which ones are the best ones to use at any given time and continually monitor...
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