Can I read Tree-Based Methods for Statistical Learning in R on EtoBox?

Tree-Based Methods for Statistical Learning in R by Brandon M. Greenwell is a nonfiction available to read on EtoBox.

What is Tree-Based Methods for Statistical Learning in R about?

The book follows up most ideas and mathematical concepts with code-based examples in the R statistical language; with an emphasis on using as few external packages as possible. For example, users will be exposed to writing their own random forest and gradient tree boosting functions using simple for loops and basic tree fitting software (like rpart and party/partykit), and more. The core chapters also end with a detailed section on relevant software in both R and other opensource alternatives (e.g., Python, Spark, and Julia), and example usage on real data sets. While the book mostly uses R, it is meant to be equally accessible and useful to non-R programmers.Consumers of this book will have gained a solid foundation (and appreciation) for tree-based methods and how they can be used to solve practical problems and challenges data scientists often face in applied work. Features: CHAPMAN & HALL/CRC DATA SCIENCE SERIES Reflecting the interdisciplinary nature of the field, this book series brings together researchers, practitioners, and instructors from statistics, computer science, machine learning, and analytics. The series will publish cutting-edge research, industry applications, a

Who reads Tree-Based Methods for Statistical Learning in R?

Author

Brandon M. Greenwell

Publisher

Chapman and Hall/CRC

Published

2022

Language

EN

ISBN

9780367532468

Category

nonfiction

Subjects

Mathematics, Computer Science, Business