DATA SCIENCE WITH MATLAB. SUPERVISED LEARNING TECHNIQUES: CLASSIFICATION

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 classification will be developed. More specifically, we will go deeper into the Generalized Linear Models, Logistic Regression, Support Vector Machine, Discriminnat Analysis, Naïve Bayes, Nearest Neighbor, Decision Tress, Regression Trees, Neural Networks for classification and other supervised techniques based in Classification. Additionaly, on work with Classification Learner to train models to classify data. Using this app, you can explore supervised machine learning using various classifiers. You can explore your data, select features, specify validation schemes, train models, and assess results.Variety of examples are solved using the MATLAB software.