Interpreting and clustering outliers with sapling random forests
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00219640" target="_blank" >RIV/68407700:21230/14:00219640 - isvavai.cz</a>
Alternative codes found
RIV/67985807:_____/14:00432410 RIV/68407700:21230/14:00219641 RIV/68407700:21240/14:00219641 RIV/68407700:21240/14:00219640
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Interpreting and clustering outliers with sapling random forests
Original language description
The main objective of outlier detection is find- ing samples considerably deviating from the majority. Such outliers, often referred to as anomalies, are nowadays more and more important, because they help to uncover in- teresting events within data. Consequently, a considerable amount of statistical and data mining techniques to iden- tify anomalies was proposed in the last few years, but only a few works at least mentioned why some sample was la- belled as an anomaly. Therefore, we propose a method based on specifically trained decision trees, called sapling random forest. Our method is able to interpret the output of arbitrary anomaly detector. The explanation is given as a subset of features, in which the sample is most deviating, or as con- junctions of atomic conditions, which can be viewed as antecedents of logical rules easily understandable by hu- mans. To simplify the investigation of suspicious samples even more, we propose two methods of clustering anoma- lies into groups. Such clusters can be investigated at once saving time and human efforts. The feasibility of our ap- proach is demonstrated on several synthetic and one real world datasets.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA13-17187S" target="_blank" >GA13-17187S: Constructing Advanced Comprehensible Classifiers</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 14th conference ITAT 2014 – Workshops and Posters
ISBN
978-80-87136-19-5
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
61-67
Publisher name
Institute of Computer Science AS CR
Place of publication
Praha
Event location
Demänovská Dolina
Event date
Sep 25, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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