Classification and Regression Trees |  | Authors: Leo Breiman, Jerome Friedman, Charles J. Stone, R.A. Olshen
Publisher: Chapman and Hall/CRC
List Price: $83.95
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Rating:  5 reviews
Sales Rank: 384710
Media: Paperback
Edition: 1
Pages: 368
Number Of Items: 1
Shipping Weight (lbs): 1.2
Dimensions (in): 9.1 x 6.1 x 0.9
ISBN: 0412048418
Dewey Decimal Number: 519.536
EAN: 9780412048418
ASIN: 0412048418
Publication Date: January 1, 1984
Availability: Usually ships in 1-2 business days
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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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| Customer Reviews:
the book that made tree classification algorithms work better through the concept of pruning January 24, 2008
Michael R. Chernick (Holland PA)
31 out of 31 found this review helpful
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.
The Original CART Resource May 30, 2007
Timothy S. Clendaniel (Baltimore City, Maryland)
2 out of 2 found this review helpful
This is the original textbook written by the pioneers of the Classification And Regression Trees algorithm, which has now been cited in over 2200 academic journals. While some of the material can be fairly complex, the authors take great pains to make the material accessible. Many examples are given, and the algorithm and process are broken down into discrete pieces. It is the single best resource I have encountered on the topic.
NOTE: One odd aspect of the text is that there has been absolutely ZERO effort has been expended on either graphic design or typesetting. Instead, it looks like a high school student typed it out late one night. If such details are important to you, you should skip this one.
A must have for all serious decision trees researchers May 5, 2000
T.S. Lim
19 out of 19 found this review helpful
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.
Instructive and Powerful April 13, 2000
Alex Horovitz (Acton, MA)
3 out of 3 found this review helpful
The book was a very good introduction to Classification andRegression Trees, and coupled with the software ( ) make for apowerful approach to solving traditional classification problems.
 tough sledding but worth it December 23, 1998
Alan Mead (amead@soltec.net) (Lockport, IL)
17 out of 17 found this review helpful
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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