DATA SCIENCE WITH MATLAB. SUPERVISED LEARNING TECHNIQUES: REGRESSION

Data science is an interdisciplinary field that employs methods, algorithms, processes, and systems to extract insights and conclusions from structured and unstructured data. It combines elements of statistics, computer science, mathematics, and analytical techniques to solve problems, make predictions, and generate value from data. Machine learning techniques play a key role within the data analysis phase of data science. In this book, supervised learning techniques related to regression will be developed. More specifically, we will go deeper into the Linear Model Regression, Neural Networks Regression, Stepwise Regression, Partial Least Square Regression PLS, LASSO regression, LARS LASSO regression, RIDGE Regression, Elastic Net Regression, Robust Regression and other supervised techniques based in Regression. Variety of examples are solved using the MATLAB software.