Mining data to find subsets of high activity.

DOI10.1016/J.JSPI.2003.06.014zbMath1040.62096OpenAlexW2048622403MaRDI QIDQ1429873

Dhammika Amaratunga

Publication date: 27 May 2004

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2003.06.014

zbMATH Keywords

Data miningARFClassification treeRecursive partitioning

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (4)

Tests and classification methods in adaptive designs with applications ⋮ Strong approximations of level exceedences related to multiple hypothesis testing ⋮ BUSDM – an algorithm for the bottom-up search of departures from a model ⋮ Optimal factorial designs for CDNA microarray experiments

Uses Software

• UCI-ml
• ElemStatLearn
• C4.5

Cites Work

• An extreme value theory for long head runs
• The Longest Run of Heads
• The Future of Data Analysis
• Printer graphics for clustering
• Problems in the Analysis of Survey Data, and a Proposal
• The elements of statistical learning. Data mining, inference, and prediction
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