Abstract
In V-detector or TMA-OR, the parameters self radius rs or Omin are required to be set by experience. To solve the problem, a novel self suppression operator based on self radius learning mechanism is proposed. The results of experiment show that the proposed algorithm is more effective than V-detector or TMA-OR when KDD and 2-dimensional synthetic data are as the data set.
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Chen, J., Zhang, S., Liu, Y. (2014). A Novel Self Suppression Operator Used in TMA. In: Corchado, E., Lozano, J.A., Quintián, H., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2014. IDEAL 2014. Lecture Notes in Computer Science, vol 8669. Springer, Cham. https://doi.org/10.1007/978-3-319-10840-7_37
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DOI: https://doi.org/10.1007/978-3-319-10840-7_37
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10839-1
Online ISBN: 978-3-319-10840-7
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