Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
SQL Server 2016 Developer's Guide

You're reading from   SQL Server 2016 Developer's Guide Build efficient database applications for your organization with SQL Server 2016

Arrow left icon
Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781786465344
Length 616 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Dejan Sarka Dejan Sarka
Author Profile Icon Dejan Sarka
Dejan Sarka
Miloš Radivojević Miloš Radivojević
Author Profile Icon Miloš Radivojević
Miloš Radivojević
William Durkin William Durkin
Author Profile Icon William Durkin
William Durkin
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Introduction to SQL Server 2016 FREE CHAPTER 2. Review of SQL Server Features for Developers 3. SQL Server Tools 4. Transact-SQL Enhancements 5. JSON Support in SQL Server 6. Stretch Database 7. Temporal Tables 8. Tightening the Security 9. Query Store 10. Columnstore Indexes 11. Introducing SQL Server In-Memory OLTP 12. In-Memory OLTP Improvements in SQL Server 2016 13. Supporting R in SQL Server 14. Data Exploration and Predictive Modeling with R in SQL Server

Chapter 14. Data Exploration and Predictive Modeling with R in SQL Server

Using the R language inside SQL Server gives us the opportunity to get knowledge out of data. We introduced R and R support in SQL Server in the previous chapter, and this chapter demonstrates how you can use R for advanced data exploration and for statistical analysis and predictive modeling, way beyond the possibilities offered by using T-SQL language only.

You will start with intermediate statistics: exploring associations between two discrete, two continuous, and one discrete and one continuous variable. You will also learn about linear regression, where you explain the values of the dependent continuous variable with a linear regression formula using one or more continuous input variables.

The second section of this chapter starts with introducing advanced multivariate data mining and machine learning methods. You will learn about methods that do not use a target variable, or so-called undirected methods...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image