Machine Learning With Random Forests And Decision Trees: A Mostly Intuitive Guide, But Also Some Python
| Author | : | |
| Rating | : | 4.31 (901 Votes) |
| Asin | : | B01JBL8YVK |
| Format Type | : | |
| Number of Pages | : | 499 Pages |
| Publish Date | : | 2017-01-05 |
| Language | : | English |
DESCRIPTION:
The reason is that those are easy to understand and they stick with you. They are typically used to categorize something based on other data that you have. This book covers how Random Forests work in an intuitive way, and also explains the equations behind many of the functions, but it only has a small amount of actual code (in python).This book is focused on giving examples and providing analogies for the most fundamental aspects of how random forests and decision trees work. Additionally, since Decision Trees are a fundamental part of R
Amazon Customer said Great starter book on the concept. Great starter book on the concept. High level selection of topics, conversational presentation, and most importantly a fast read. This is an excellent strategy because it covers all the essentials, while still leaving you enough time to dig into some application or play with a . "Easy introduction" according to Edem Togbey. This book is well written and it is an easy introduction to the concepts introduced.I would recommend it if you are just trying to have a better sense of the principles of Random Forest algorithm. You are not going to become an expert in the subject just by reading it.. Amazon Customer said Just what i needed. This book have a great background into decision trees and how they are used in random forest. At the end of the book they also give recommendations for further reading. Great stuff.