Description

An Introduction to Statistical Learning offers a clear overview of the area of statistical learning, which is crucial for making sense of the enormous and complicated data sets that have evolved in a variety of fields over the past 20 years, including biology, economics, marketing, and astrophysics. Some of the most significant modelling and prediction strategies are covered in this book, along with pertinent applications. There are several topics covered, including as multiple testing, survival analysis, resampling techniques, shrinkage techniques, support vector machines, clustering, and linear regression. The methodologies are illustrated with colour graphics and actual-world instances. Each chapter of this book includes exercises to help practitioners in science, business, and other sectors more easily employ these statistical learning techniques.