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Erschienen in:
Neural Networks – State of Art, Brief History, Basic Models and Architecture Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Ensembles of Heterogeneous Concept Drift Detectors - Experimental Study

verfasst von : Michał Woźniak, Paweł Ksieniewicz, Bogusław Cyganek, Krzysztof Walkowiak

Erschienen in: Computer Information Systems and Industrial Management

Verlag: Springer International Publishing

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Abstract

For the contemporary enterprises, possibility of appropriate business decision making on the basis of the knowledge hidden in stored data is the critical success factor. Therefore, the decision support software should take into consideration that data usually comes continuously in the form of so-called data stream, but most of the traditional data analysis methods are not ready to efficiently analyze fast growing amount of the stored records. Additionally, one should also consider phenomenon appearing in data stream called concept drift, which means that the parameters of an using model are changing, what could dramatically decrease the analytical model quality. This work is focusing on the classification task, which is very popular in many practical cases as fraud detection, network security, or medical diagnosis. We propose how to detect the changes in the data stream using combined concept drift detection model. The experimental evaluations confirm its pretty good quality, what encourage us to use it in practical applications.

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Vorheriges Kapitel Classification of Protein Interactions Based on Sparse Discriminant Analysis and Energetic Features
Nächstes Kapitel Harmony Search for Data Mining with Big Data
Fußnoten
1
We assume continuous attributes, but for discrete ones we have to take into consideration corresponding conditional probabilities p(x|j).
 
2
We assume so-called 0–1 loss function. For different loss function the optimal algorithm minimizes so-called overall risk [4].
 
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Metadaten
Titel
Ensembles of Heterogeneous Concept Drift Detectors - Experimental Study
verfasst von
Michał Woźniak
Paweł Ksieniewicz
Bogusław Cyganek
Krzysztof Walkowiak
Copyright-Jahr
2016
Buch
Computer Information Systems and Industrial Management

Print ISBN: 978-3-319-45377-4

Electronic ISBN: 978-3-319-45378-1

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-45378-1_48

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