Classification and Regression Trees (Paperback)

by Leo Breiman (Author), Jerome Friedman (Author), Charles J. Stone (Author), R.A. Olshen (Author) "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..." (more)
Key Phrases: digit recognition data, variable misclassification costs, optimally pruned subtree, Data Missing, San Diego, University of California (more...)

Editorial Reviews

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.

Product Details

• Paperback: 368 pages
• Publisher: Chapman & Hall/CRC; 1 edition (January 1, 1984)
• Language: English
• ISBN-10: 0412048418
• ISBN-13: 978-0412048418
• Product Dimensions: 9.1 x 6.1 x 0.9 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 4.8 out of 5 stars See all reviews (6 customer reviews)
• Amazon.com Sales Rank: #517,249 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

28 of 28 people found the following review helpful:

5.0 out of 5 stars the book that made tree classification algorithms work better through the concept of pruning, January 24, 2008

By	Michael R. Chernick "statman31147" (Holland PA) - See all my reviews (REAL NAME)

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.

22 of 22 people found the following review helpful:

5.0 out of 5 stars the book that made tree classification rigorous, April 5, 2001

By	Michael R. Chernick "statman13" (Malvern, PA) - See all my reviews (REAL NAME)

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 farther 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 17 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.

17 of 17 people found the following review helpful:

5.0 out of 5 stars A must have for all serious decision trees researchers, May 5, 2000

By	T.S. Lim - See all my reviews

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.