# Classification and Regression Trees

@inproceedings{Breiman1984ClassificationAR, title={Classification and Regression Trees}, author={L. Breiman and Jerome H. Friedman and Richard A. Olshen and C. J. Stone}, year={1984} }

Background. Introduction to Tree Classification. Right Sized Trees and Honest Estimates. Splitting Rules. Strengthening and Interpreting. Medical Diagnosis and Prognosis. Mass Spectra Classification. Regression Trees. Bayes Rules and Partitions. Optimal Pruning. Construction of Trees from a Learning Sample. Consistency. Bibliography. Notation Index. Subject Index.

## 14,833 Citations

### Classification and Regression Tree Methods

- Computer Science
- 2008

This article discusses the C4.5, CART, CRUISE, GUIDE, and QUEST methods in terms of their algorithms, features, properties, and performances.

### Classification and Regression Trees

- Computer Science
- 2014

CART is a method that provides mechanisms for building a custom-specific, nonparametric estimation model based solely on the analysis of measurement project data, called training data.

### Classification and Regression Trees

- Mathematics
- 2000

We will call an estimator for the regression function defined by the CART methodology a regression tree. The word CART means classification and regression tree. This chapter will focus only on the…

### Cost-Sensitive Pruning of Decision Trees

- Computer ScienceECML
- 1994

This paper shows how the misclassification costs, a related criterion applied if errors vary in their costs, can be integrated in several well-known pruning techniques.

### Survival Trees by Goodness of Split

- Computer Science
- 1993

Abstract A tree-based method for censored survival data is developed, based on maximizing the difference in survival between groups of patients represented by nodes in a binary tree. The method…

### Selecting the best categorical split for classification trees

- Computer Science
- 2001

Based on a family of splitting criteria for classification trees, methods of selecting the best categorical splits are studied. They are shown to be very useful in reducing the computational…

### Data Mining Classification : Basic Concepts , Decision Trees , and Model Evaluation

- Computer Science
- 2004

Classification, which is the task of assigning objects to one of several predefined categories, is a pervasive problem that encompasses many diverse applications. Examples include detecting spam…

### Randomization in Aggregated Classification Trees

- Computer Science
- 2005

This paper discusses and compares different methods for model aggregation, and addresses the problem of finding minimal number of trees sufficient for the forest.

### Using Model Trees for Classification

- Computer ScienceMachine Learning
- 2004

Surprisingly, using this simple transformation the model tree inducer M5′, based on Quinlan's M5, generates more accurate classifiers than the state-of-the-art decision tree learner C5.0, particularly when most of the attributes are numeric.

### Classification Based on Tree-Structured Allocation Rules

- Business
- 2008

The authors consider the problem of classifying an unknown observation into 1 of several populations by using tree-structured allocation rules. Although many parametric classification procedures are…

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This heuristic approach to the problem of conversion of decision tables to decision trees is treated and has low design complexity and yet provides near-optimal decision trees.

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A nonparametric algorithm is presented for the hierarchical partitioning of the feature space that generates an efficient partitioning tree for specified probability of error by maximizing the amount of average mutual information gain at each partitioning step.

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