Abstract
Dimension reduction of data is an important issue in the data processing and it is needed for the analysis of higher dimensional data in the application domains. Rough set is fundamental and useful to reduce higher dimensional data to lower one. Reduct in the rough set is a minimal subset of features, which has the same discernible power as the entire features in the higher dimensional scheme. It is shown that nearest neighbor relation with minimal distance proposed here has a fundamental information for classification. In this paper, the nearest neighbor relation plays a fundamental role for generation of reducts using the Boolean reasoning. Then, two reduct generation methods based on the nearest neighbor relation with minimal distance are proposed here, which are derived from Boolean expression of nearest neighbor relations and their operations.
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Ishii, N., Torii, I., Iwata, K., Odagiri, K., Nakashima, T. (2017). Generation of Reducts Based on Nearest Neighbor Relations and Boolean Reasoning. In: MartÃnez de Pisón, F., Urraca, R., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2017. Lecture Notes in Computer Science(), vol 10334. Springer, Cham. https://doi.org/10.1007/978-3-319-59650-1_33
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DOI: https://doi.org/10.1007/978-3-319-59650-1_33
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