Random Forests with R is popular PDF and ePub book, written by Robin Genuer in 2020-09-10, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Random Forests with R can be Read Online from any device for your convenience.

Random Forests with R Book PDF Summary

This book offers an application-oriented guide to random forests: a statistical learning method extensively used in many fields of application, thanks to its excellent predictive performance, but also to its flexibility, which places few restrictions on the nature of the data used. Indeed, random forests can be adapted to both supervised classification problems and regression problems. In addition, they allow us to consider qualitative and quantitative explanatory variables together, without pre-processing. Moreover, they can be used to process standard data for which the number of observations is higher than the number of variables, while also performing very well in the high dimensional case, where the number of variables is quite large in comparison to the number of observations. Consequently, they are now among the preferred methods in the toolbox of statisticians and data scientists. The book is primarily intended for students in academic fields such as statistical education, but also for practitioners in statistics and machine learning. A scientific undergraduate degree is quite sufficient to take full advantage of the concepts, methods, and tools discussed. In terms of computer science skills, little background knowledge is required, though an introduction to the R language is recommended. Random forests are part of the family of tree-based methods; accordingly, after an introductory chapter, Chapter 2 presents CART trees. The next three chapters are devoted to random forests. They focus on their presentation (Chapter 3), on the variable importance tool (Chapter 4), and on the variable selection problem (Chapter 5), respectively. After discussing the concepts and methods, we illustrate their implementation on a running example. Then, various complements are provided before examining additional examples. Throughout the book, each result is given together with the code (in R) that can be used to reproduce it. Thus, the book offers readers essential information and concepts, together with examples and the software tools needed to analyse data using random forests.

Detail Book of Random Forests with R PDF

Random Forests with R
  • Author : Robin Genuer
  • Release : 10 September 2020
  • Publisher : Springer Nature
  • ISBN : 9783030564858
  • Genre : Mathematics
  • Total Page : 107 pages
  • Language : English
  • PDF File Size : 21,8 Mb

If you're still pondering over how to secure a PDF or EPUB version of the book Random Forests with R by Robin Genuer, don't worry! All you have to do is click the 'Get Book' buttons below to kick off your Download or Read Online journey. Just a friendly reminder: we don't upload or host the files ourselves.

Get Book

Random Forests with R

Random Forests with R Author : Robin Genuer,Jean-Michel Poggi
Publisher : Springer Nature
File Size : 55,9 Mb
Get Book
This book offers an application-oriented guide to random forests: a statistical learning method exte...

Random Forests

Random Forests Author : Yu. L. Pavlov
Publisher : Walter de Gruyter GmbH & Co KG
File Size : 31,7 Mb
Get Book
No detailed description available for "Random Forests"....

TensorFlow Machine Learning Projects

TensorFlow Machine Learning Projects Author : Ankit Jain,Armando Fandango,Amita Kapoor
Publisher : Packt Publishing Ltd
File Size : 42,6 Mb
Get Book
Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and Ten...

Hands On Machine Learning with R

Hands On Machine Learning with R Author : Brad Boehmke,Brandon M. Greenwell
Publisher : CRC Press
File Size : 33,9 Mb
Get Book
Hands-on Machine Learning with R provides a practical and applied approach to learning and developin...

Computational Genomics with R

Computational Genomics with R Author : Altuna Akalin
Publisher : CRC Press
File Size : 18,8 Mb
Get Book
Computational Genomics with R provides a starting point for beginners in genomic data analysis and a...

Multiple Classifier Systems

Multiple Classifier Systems Author : Josef Kittler,Fabio Roli
Publisher : Springer
File Size : 33,6 Mb
Get Book
Driven by the requirements of a large number of practical and commercially - portant applications, t...

Machine Learning ECML 2004

Machine Learning  ECML 2004 Author : Jean-Francois Boulicaut,Floriana Esposito,Fosca Giannotti,Dino Pedreschi
Publisher : Springer
File Size : 10,6 Mb
Get Book
The proceedings of ECML/PKDD 2004 are published in two separate, albeit - tertwined,volumes:theProce...

Ensemble Machine Learning

Ensemble Machine Learning Author : Cha Zhang,Yunqian Ma
Publisher : Springer Science & Business Media
File Size : 42,6 Mb
Get Book
It is common wisdom that gathering a variety of views and inputs improves the process of decision ma...