Abstract
Discriminant analysis is an effective methodology to deal with the classification problem. However, most common methods including binary logistic regression in discriminant analysis rarely consider the semantics explanations such as losses or costs in decision rules. From the idea of three-way decisions in decision-theoretic rough sets (DTRS), we propose a new discriminant analysis approach by combining DTRS and binary logistic regression. DTRS is utilized to systematically calculate the corresponding thresholds with Bayesian decision procedure. Meanwhile, the binary logistic regression is employed to compute the conditional probability of three-way decisions. An empirical study validates the reasonability and effectiveness of the proposed approach.
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Liu, D., Li, T., Liang, D. (2011). A New Discriminant Analysis Approach under Decision-Theoretic Rough Sets. In: Yao, J., Ramanna, S., Wang, G., Suraj, Z. (eds) Rough Sets and Knowledge Technology. RSKT 2011. Lecture Notes in Computer Science(), vol 6954. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24425-4_62
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DOI: https://doi.org/10.1007/978-3-642-24425-4_62
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