Abstract
We propose a new classifier ARTMAP2-AW based on adaptive resonance theory. ARTMAP2-AW evaluates the degree of importance of each attribute, and on the basis of the importance, attributes irrelevant to classification are detected for efficient learning. Experimental results show that ARTMAP2-AW acquires better classification rules than well-known classifiers.
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Ueda, H., Nasu, Y., Mikura, Y., Takahashi, K. (2008). Online Classifier Considering the Importance of Attributes. In: Ho, TB., Zhou, ZH. (eds) PRICAI 2008: Trends in Artificial Intelligence. PRICAI 2008. Lecture Notes in Computer Science(), vol 5351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89197-0_113
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DOI: https://doi.org/10.1007/978-3-540-89197-0_113
Publisher Name: Springer, Berlin, Heidelberg
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