Regression Analysis with R
Design and develop statistical nodes to identify unique relationships within data at scale
1st Edition
Published on 23. September 2024
422 pages
978-1-78862-270-7 (ISBN)
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Giuseppe Ciaburro
Regression Analysis with R
Book
01/2018
Packt Publishing
€52.00
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Person
Ciaburro Giuseppe :
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).
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).
Content
Table of Contents - Getting Started with Regression
- Basic Concepts
- More Than Just One Predictor
- When the Response Falls into Two Categories
- Data Preparation Using R Tools
- Avoiding Overfitting Problems - Achieving Generalization
- Going Further with Regression Models
- Beyond Linearity
- Regression Analysis in Practice
- Basic Concepts
- More Than Just One Predictor
- When the Response Falls into Two Categories
- Data Preparation Using R Tools
- Avoiding Overfitting Problems - Achieving Generalization
- Going Further with Regression Models
- Beyond Linearity
- Regression Analysis in Practice
