Data Mining Tools and Datasets

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Tools:

$\triangleright$: C4.5: This is a link to Ross Quinlan's home page and the C4.5 decsision tree program that he created. [NOTE: Source code is available. Can be compiled on Windows and Unix platforms.]
$\triangleright$: MLC++: Provides a suite of machine learning algorithms including decision tree based classification, nearest neighbor (instance-based) classifiers, and naive bayesian classifier. [NOTE: Source code is available. Can be compiled on many Unix platforms.]
$\triangleright$: SIPINA_W: Provides a suite of classification algorithms including CART, ID3, C4.5, and ChAID implementations. [NOTE: Only binary executable is available for Windows]
$\triangleright$: OC1: Provides algorithms for building decision trees that contain linear combination of one or more attributes at each internal node. [NOTEs: Source code available. Unix platform.]
$\triangleright$: Weka: Provides machine learning techniques for instance based classification (PEBLS, K*), rule based classification (FOIL), etc. [NOTEs: Unix platform]
$\triangleright$: DBMiner: A suite of data mining tools for various tasks including classification, market basket analysis (association rules), prediction. [NOTEs: Only binary executable is available for Windows NT]

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Datasets:

$\triangleright$: UCI Machine Learning Repository: Around 70 datasets are available for the purpose of evaluating learning algorithms. Read the README and SUMMARY-TABLE files as a good starting point.

Prepared By Mahesh Joshi. Please mail any additions/corrections.