Title
Instant exceptional model ining using weighted controlled pattern sampling Instant exceptional model ining using weighted controlled pattern sampling
Author
Faculty/Department
Faculty of Sciences. Mathematics and Computer Science
Publication type
conferenceObject
Publication
Cham :Springer int publishing ag ,
Subject
Computer. Automation
Source (journal)
ADVANCES IN INTELLIGENT DATA ANALYSIS XIII
Source (book)
13th International Symposium on Intelligent Data Analysis (IDA), OCT 30-NOV 01, 2014, Fac Club, Leuven, BELGIUM
Volume/pages
8819(2014) , p. 203-214
ISSN
0302-9743
ISBN
978-3-319-12571-8
ISI
000350861600018
ISBN
978-3-319-12570-1
Carrier
E
Target language
English (eng)
Affiliation
University of Antwerp
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.
E-info
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Handle