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combining models 2 Distributed anomaly detection 1 classification 1 classifier ensembles 1 decision trees 1 global anomalies 1 machine learning 1 model trees 1 rotation-based ensemble 1
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Article 2
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FU, YAN 1 HSU, KUO-WEI 1 Kotsiantis, S.B. 1 LAZAREVIC, ALEKSANDAR 1 SRIVASTAVA, JAIDEEP 1 WU, YUE 1 ZHOU, JUNLIN 1
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International Journal of Data Analysis Techniques and Strategies 1 International Journal of Information Technology & Decision Making (IJITDM) 1
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RePEc 2
Showing 1 - 2 of 2
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Rotation-based model trees for classification
Kotsiantis, S.B. - In: International Journal of Data Analysis Techniques and … 2 (2010) 1, pp. 22-37
Structurally, a model tree is a regression method that takes the form of a decision tree with linear regression functions instead of terminal class values at its leaves. In this study, model trees were coupled with a rotation-based ensemble for solving classification problems. In order to apply...
Persistent link: https://www.econbiz.de/10008755526
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UNSUPERVISED LEARNING BASED DISTRIBUTED DETECTION OF GLOBAL ANOMALIES
ZHOU, JUNLIN; LAZAREVIC, ALEKSANDAR; HSU, KUO-WEI; … - In: International Journal of Information Technology & … 09 (2010) 06, pp. 935-957
Anomaly detection has recently become an important problem in many industrial and financial applications. Very often, the databases from which anomalies have to be found are located at multiple local sites and cannot be merged due to privacy reasons or communication overhead. In this paper, a...
Persistent link: https://www.econbiz.de/10008690097
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