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MATLAB for Machine Learning

You're reading from   MATLAB for Machine Learning Practical examples of regression, clustering and neural networks

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781788398435
Length 382 pages
Edition 1st Edition
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Authors (2):
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 Kolluru Kolluru
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Kolluru
Giuseppe Ciaburro Giuseppe Ciaburro
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Giuseppe Ciaburro
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Table of Contents (17) Chapters Close

Title Page
Credits
Foreword
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Getting Started with MATLAB Machine Learning FREE CHAPTER 2. Importing and Organizing Data in MATLAB 3. From Data to Knowledge Discovery 4. Finding Relationships between Variables - Regression Techniques 5. Pattern Recognition through Classification Algorithms 6. Identifying Groups of Data Using Clustering Methods 7. Simulation of Human Thinking - Artificial Neural Networks 8. Improving the Performance of the Machine Learning Model - Dimensionality Reduction 9. Machine Learning in Practice

Importing data into MATLAB


In data analysis, a fundamental role is assumed by the exchange of such data between the analysis environment and external devices. We start from data collection and importing in MATLAB for whatever analysis we are going to do--always. As well, we will finish our activities by exporting the results. There are several ways to import and export data in the MATLAB environment depending on the different formats in which data is available. In this section, we will cover data import.

The Import Wizard

We can import files into MATLAB both interactively and programmatically. Interactively, we can import data from a disk file or the system clipboard. From a file, do any one of these three actions:

  • On the HOME tab, in the Variable section, select Import Data.
  • Double-click on a filename in the Current Folder browser.
  • Call the uiimport() function via the command line.

From the clipboard, do any one of the two following actions:

  • On the Workspace browser title bar, click on the triangle...
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