Publication
Title
Instant exceptional model ining using weighted controlled pattern sampling
Author
Abstract
When plugged into instant interactive data analytics processes, pattern mining algorithms are required to produce small collections of high quality patterns in short amounts of time. In the case of Exceptional Model Mining (EMM), even heuristic approaches like beam search can fail to deliver this requirement, because in EMM each search step requires a relatively expensive model induction. In this work, we extend previous work on high performance controlled pattern sampling by introducing extra weighting functionality, to give more importance to certain data records in a dataset. We use the extended framework to quickly obtain patterns that are likely to show highly deviating models. Additionally, we combine this randomized approach with a heuristic pruning procedure that optimizes the pattern quality further. Experiments show that in contrast to traditional beam search, this combined method is able to find higher quality patterns using short time budgets.
Language
English
Source (journal)
Lecture notes in computer science. - Berlin, 1973, currens
Source (book)
13th International Symposium on Intelligent Data Analysis (IDA), OCT 30-NOV 01, 2014, Fac Club, Leuven, BELGIUM
Publication
Cham : Springer int publishing ag, 2014
ISBN
978-3-319-12571-8
Volume/pages
8819(2014), p. 203-214
ISI
000350861600018
Number
978-3-319-12570-1
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 12.05.2015
Last edited 22.07.2017
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