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F# for Machine Learning Essentials

You're reading from  F# for Machine Learning Essentials

Product type Book
Published in Feb 2016
Publisher
ISBN-13 9781783989348
Pages 194 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Sudipta Mukherjee Sudipta Mukherjee
Profile icon Sudipta Mukherjee
LinkedIn
Sudipta Mukherjee was born in Kolkata and migrated to Bangalore. He is an electronics engineer by education and a computer engineer/scientist by profession and passion. He graduated in 2004 with a degree in electronics and communication engineering. He has a keen interest in data structure, algorithms, text processing, natural language processing tools development, programming languages, and machine learning at large. His first book on Data Structure using C has been received quite well. Parts of the book can be read on Google Books. The book was also translated into simplified Chinese, available from Amazon.cn. This is Sudipta's second book with Packt Publishing. His first book, .NET 4.0 Generics , was also received very well. During the last few years, he has been hooked to the functional programming style. His book on functional programming, Thinking in LINQ, was released in 2014. He lives in Bangalore with his wife and son. Sudipta can be reached via e-mail at sudipto80@yahoo.com and via Twitter at @samthecoder.
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Table of Contents (16) Chapters

F# for Machine Learning Essentials
Credits
Foreword
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
1. Introduction to Machine Learning 2. Linear Regression 3. Classification Techniques 4. Information Retrieval 5. Collaborative Filtering 6. Sentiment Analysis 7. Anomaly Detection Index

Multivariate multiple linear regression

When you want to predict multiple target values for the same set of predictor variables, you need to use multivariate multiple linear regression. Multivariate linear regression takes an array of a set of predictors and an associated list of outcomes for each of this predictor set of values.

In this example, we will use Accord.NET to find the relationships between several data:

  1. Get Accord Statistics via NuGet by giving the following command in PM console:

    PM> Install-Package Accord.Statistics -Version 2.15.0

  2. Once you install this package, the following code finds coefficients of the multivariate linear regression for sample data:

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Authors (1)

Profile icon Sudipta Mukherjee
LinkedIn
Sudipta Mukherjee was born in Kolkata and migrated to Bangalore. He is an electronics engineer by education and a computer engineer/scientist by profession and passion. He graduated in 2004 with a degree in electronics and communication engineering. He has a keen interest in data structure, algorithms, text processing, natural language processing tools development, programming languages, and machine learning at large. His first book on Data Structure using C has been received quite well. Parts of the book can be read on Google Books. The book was also translated into simplified Chinese, available from Amazon.cn. This is Sudipta's second book with Packt Publishing. His first book, .NET 4.0 Generics , was also received very well. During the last few years, he has been hooked to the functional programming style. His book on functional programming, Thinking in LINQ, was released in 2014. He lives in Bangalore with his wife and son. Sudipta can be reached via e-mail at sudipto80@yahoo.com and via Twitter at @samthecoder.
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See other products by Sudipta Mukherjee

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