Abstract
Following paper presents Exposer Ensemble (ee), being a combined classifier based on the original model of quantized subspace class distribution. It presents a method of establishing and processing the Planar Exposer – base representation of discrete class distribution over given subspace, and a proposition how to effectively fuse discriminatory power of many Planar Exposers into a combined classifier. The natural property of the representation used in the following article is its resistance to the imbalance of training data, without the need to use over- or undersampling methods and the constant computational complexity of prediction. Description of proposed algorithm is complemented by a series of computer experiments conducted on the collection of balanced and imbalanced datasets with diverse imbalance ratio, proving its usefulness in a supervised learning task.
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The work was funded by the statutory funds of Department of Systems and Computer Networks (Faculty of Electronics, Wrocław University of Science and Technology) during realization of Mloda Kadra 2017/2018 task.
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Ksieniewicz, P. (2018). Combined Classifier Based on Quantized Subspace Class Distribution. In: Yin, H., Camacho, D., Novais, P., Tallón-Ballesteros, A. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2018. IDEAL 2018. Lecture Notes in Computer Science(), vol 11314. Springer, Cham. https://doi.org/10.1007/978-3-030-03493-1_79
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