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You're reading from  MATLAB for Machine Learning - Second Edition

Product typeBook
Published inJan 2024
Reading LevelIntermediate
PublisherPackt
ISBN-139781835087695
Edition2nd Edition
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Giuseppe Ciaburro
Giuseppe Ciaburro
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Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).
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Feature selection and feature extraction using MATLAB

In MATLAB, there are several built-in functions and toolboxes that can be used for dimensionality reduction. In the next section, we will explore some practical examples of the dimensionality reduction algorithm in the MATLAB environment.

Stepwise regression for feature selection

Regression analysis is a valuable approach for understanding the impact of independent variables on a dependent variable. It allows us to identify predictors that hold greater influence over the model’s response. Stepwise regression is a variable selection method used to choose a subset of predictors that exhibit the strongest relationship with the dependent variable. There are three common variable selection algorithms:

  • Forward method: The forward method starts with an empty model, where no predictors are initially selected. In the first step, the variable showing the most significant association at a statistical level is added. In...
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MATLAB for Machine Learning - Second Edition
Published in: Jan 2024Publisher: PacktISBN-13: 9781835087695

Author (1)

author image
Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).
Read more about Giuseppe Ciaburro