- Paperback: 368 pages
- Publisher: Chapman and Hall/CRC; New edition edition (1 Jan 1984)
- Language English
- ISBN-10: 0412048418
- ISBN-13: 978-0412048418
- Product Dimensions: 23.9 x 15.2 x 2 cm
- Average Customer Review: 4.0 out of 5 stars See all reviews (1 customer review)
- Amazon Bestsellers Rank: 658,906 in Books (See Top 100 in Books)
- See Complete Table of Contents
Classification and Regression Trees
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Product Description
Product Description
The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
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First Sentence
At the University of California, San Diego Medical Center, when a heart attack patient is admitted, 19 variables are measured during the first 24 hours. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
At the University of California, San Diego Medical Center, when a heart attack patient is admitted, 19 variables are measured during the first 24 hours. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Customer Reviews
Most Helpful Customer Reviews
2 of 3 people found the following review helpful
Format:Paperback
The bible of CART, if you intend implementing a CART program yourself, or if you need to understand how CART works, then you'll find this very helpful. Unfortunately the typeface is old typewriter style, and the sometimes illogical use of symbols, superscripts and subscripts can be confusing, but, so far, there's no other reference book on this subject to match.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
6 reviews
34 of 34 people found the following review helpful
the book that made tree classification algorithms work better through the concept of pruning
24 Jan 2008
Format:Paperback
In 1984 Brieman, Olshen, Friedman and Stone published this book and produced a software product called CART that made tree classification popular. These algorithms were very useful in medical applications and the book illustrated some simple success stories particularly ones from Richard Olshen's experience working in the Medical School at UC San Diego.
Olshen and Gordon did some of the work on the asymptotic theory of recursive partitioning that made the methodology credible to the statistical research community. The methods began to be applied to pattern recognition problems and also to the development of expert systems. Today data miners use these tools.
These ideas goes back a lot further than these authors. However, previous attempts at recursive partitioning algorithms tended to grow trees with too many terminal nodes. These authors introduced two important ideas. One was to grow the trees overly long and then prune them back. The second was to continually use cross-validation to evaluate the trees.
This book is still very valuable 24 years after it was first published. It is also readible by general audiences for the most part. It now stands as a classic text on the subject of classification and regression trees. There are also books that followed in its footsteps and other places where tree structure comes into play.
Olshen and Gordon did some of the work on the asymptotic theory of recursive partitioning that made the methodology credible to the statistical research community. The methods began to be applied to pattern recognition problems and also to the development of expert systems. Today data miners use these tools.
These ideas goes back a lot further than these authors. However, previous attempts at recursive partitioning algorithms tended to grow trees with too many terminal nodes. These authors introduced two important ideas. One was to grow the trees overly long and then prune them back. The second was to continually use cross-validation to evaluate the trees.
This book is still very valuable 24 years after it was first published. It is also readible by general audiences for the most part. It now stands as a classic text on the subject of classification and regression trees. There are also books that followed in its footsteps and other places where tree structure comes into play.
20 of 21 people found the following review helpful
A must have for all serious decision trees researchers
5 May 2000
Format:Paperback
This book is a must-have for all serious decision trees researchers. It explains the underlying algorithms of classification and regression trees methods in details. It's not for beginners though. It's a bit outdated by now as trees methodology has advanced much with the invention of boosting, bagging, and arcing.
19 of 20 people found the following review helpful
tough sledding but worth it
23 Dec 1998
Format:Paperback
A good introduction to classification and regression trees with a variety of examples. You need never regress again! Many will find some of the technical topics difficult but then I found the statistical grounding to be rewarding in the end. My only complaint is that the book is near worthless to practitioners like myself without software which is a little hard to find and then pricey.
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