C4.5: Programs for Machine Learning | RDL Research Database

Abstract

Classifier systems play a major role in machine learning and knowledge-based systems, and Ross Quinlan's work on ID3 and C4.5 is widely acknowledged to have made some of the most significant contributions to their development. This book is a complete guide to the C4.5 system as implemented in C for the UNIX environment. It contains a comprehensive guide to the system's use , the source code (about 8,800 lines), and implementation notes. The source code and sample datasets are also available for download (see below). C4.5 starts with large sets of cases belonging to known classes. The cases,

Keywords

Computer scienceUnixClassifier (UML)Machine learningArtificial intelligenceSource codeWorkstationSoftwareDecision treeSample (material)Software engineeringData miningProgramming languageOperating system

Affiliated Institutions

The University of Sydney AU

Related Publications

Programs for Machine Learning

Steven L. Salzberg , Alberto M. Segre

Algorithms for constructing decision trees are among the most well known and widely used of all machine learning methods. Among decision tree algorithms, J. Ross Quinlan's ID3 a...

1994 5793 citations

Open source clustering software

Michiel de Hoon , Seiya Imoto , John P. Nolan +1 more

Abstract Summary: We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable f...

2004 Bioinformatics 3113 citations

InterProScan 5: genome-scale protein function classification

Philip Jones , David Binns , Hsin-Yu Chang +14 more

Abstract Motivation: Robust large-scale sequence analysis is a major challenge in modern genomic science, where biologists are frequently trying to characterize many millions of...

2014 Bioinformatics 9048 citations

Categorical Data Analysis

Alan Agresti

Preface. 1. Introduction: Distributions and Inference for Categorical Data. 1.1 Categorical Response Data. 1.2 Distributions for Categorical Data. 1.3 Statistical Inference for ...

2002 Wiley series in probability and stati... 6519 citations

Scikit-learn: Machine Learning in Python

Fabián Pedregosa , Gaël Varoquaux , Alexandre Gramfort +13 more

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focu...

2012 arXiv (Cornell University) 62986 citations

Publication Info

Year: 1992
Type: book
Citations: 23665
Access: Closed

External Links

Citation Metrics

23665

OpenAlex

Cite This

APA Style

                            
                                    J. R. Quinlan
                                
                            (1992). 
                            C4.5: Programs for Machine Learning. 
                            
                            .