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Heterogeneous Classifier Dynamic Ensemble Algorithm based on Margin

Published: 22 October 2019 Publication History

Abstract

Ensemble learning can improve the generalization ability of the system and improve the classification performance of the system. Although the technology has been widely developed, the generalized ensemble learning algorithm has poor generalization performance, sensitivity to noise, and "false neighborhood" phenomenon. Based on this, a margin-based dynamic ensemble algorithm for heterogeneous classifiers is proposed. Based on the margin-based heterogeneous classifier, the algorithm introduces two prototype selection mechanisms: edited nearest neighbor and adaptive nearest neighbor, which make the algorithm more stable and the classifier's capability evaluation more accurate. The effectiveness of the proposed algorithm is verified by experiments and analysis in the UCI dataset.

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  1. Heterogeneous Classifier Dynamic Ensemble Algorithm based on Margin

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    CSAE '19: Proceedings of the 3rd International Conference on Computer Science and Application Engineering
    October 2019
    942 pages
    ISBN:9781450362948
    DOI:10.1145/3331453
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    Published: 22 October 2019

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    Author Tags

    1. Dynamic Ensemble
    2. Heterogeneous Classifier
    3. Margin
    4. Noise
    5. Prototype Selection

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