Abstract
Algorithm which has taken the third place in “JRS 2012 Data Mining Competition” among 126 participants is described. The competition was related to the problem of predicting topical classification of scientific publications in a field of biomedicine. The presented algorithm is a combination (blend) of simple classification algorithms: a linear classifier, a k-NN classifier and two SVMs. We build the combination using special estimation matrices. It proves again that combinations have significantly better performance compared to their individual members.
This work was supported by the Russian Foundation for Basic Research, project 12-07-00187; by the President of the Russian Federation, project MD-757.2011.9. The author is also grateful to the organizers of “JRS 2012 Data Mining Competition” for running the interesting competition. Finally, we want to thank all the active participants of the challenge for their efforts.
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D’yakonov, A. (2012). A Blending of Simple Algorithms for Topical Classification. In: Yao, J., et al. Rough Sets and Current Trends in Computing. RSCTC 2012. Lecture Notes in Computer Science(), vol 7413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32115-3_51
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DOI: https://doi.org/10.1007/978-3-642-32115-3_51
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