Chapter Six of Introduction to Machine Learning - Notes by Nils J. Nilsson.

Comparison between the "bottom up" hierarchical clustering approach and "top down" splitting as used in decision tree segmentation.

CRUISE is a statistical decision tree algorithm for classification. It is an improved descendant of an older algorithm called FACT.

Article by Carole Matthews about using decision trees for decision making.

This paper presents an alternative way of representing and solving the decision tree for nontechnical audiences.

Decision trees provide an effective structure in which alternative decisions and the implications of taking those decisions can be laid down and evaluated. They also help you to form an accurate, balanced picture of the risks and rewards that can result from a particular choice.

Decision tree page from Wikipedia, the free encyclopedia

ODBCMine generates decision trees from ODBC databases using the C4.5 data-mining algorithm.

DTREG generates a Decision Tree Forest that is an ensemble (collection) of decision trees whose predictions are combined to make the overall prediction for the forest.

Presents methods for analyzing decision trees, including exercises with solutions.

Decision tree information page from Answers.com

OR-Notes by J. R. Beasley. In many problems chance (or probability) plays an important role. Decision analysis is the general name that is given to techniques for analysing problems containing risk/uncertainty/probabilities. Decision trees are one specific decision analysis technique and we will illustrate the technique by use of an example.

A collection of links about usage of decision trees in machine learning.

Tutorial Slides by Andrew Moore. A self-contained introduction to the flavor and terminology of data mining.

This paper addresses the problem of decision tree construction in mining streaming data and introduces two new techniques that improve the efficiency of Domingos and Hulten algorithm.

An applet which solves extensive form games (multi-player decision trees).

An alternative to ID3 method of building decision trees that uses a genetic algorithm.

Full text of the article, 'A decision-tree-based symbolic rule induction system for text categorization' from IBM Systems Journal, a publication in the field of Computers & Technology, is provided free of charge by LookSmart's FindArticles service.

ITI (Incremental Tree Inducer) - a program that constructs decision trees automatically from labeled examples.

Data Mining Tools See5 and C5.0 - classifiers that are expressed as decision trees or sets of if-then rules.

Lecture about decision trees by Amos Storkey.

Meta Decision Trees are a novel method for combining multiple classifiers. MDT leaves specify which base-level classifier should be used, instead of predicting the class value directly.

PhD Thesis - Kolluru Venkata Sreerama Murthy

From Howard J. Hamilton's CS Course: Knowledge Discovery in Databases.

A Framework for Fast Decision Tree Construction of Large Datasets

List of references related to Decision Trees by F. Höppner.

Advanced analysis model included in SAS Enterprise Miner.

SGI's MineSet Tree Visualizer for viewing decision-trees.

OC1 (Oblique Classifier 1) is a decision tree induction system designed for applications where the instances have numeric (continuous) feature values. It builds decision trees that contain linear combinations of one or more attributes at each internal node.

This webpage is intended to supplement Chapter 3: Decision Tree Learning of Tom Mitchell's Machine Learning. It follows the general structure of the chapter, but provides links to pages that elaborate on topics.

Decision tree analysis software.

Add-In for Excel that helps you build a decision tree diagram in an Excel worksheet using dialog boxes.

Software for management decision analysis.