Feature selection based on logistic regression for 2-class classification of multidimensional molecular data

Sebastian Student; Alicja Płuciennik; Michał Jakubczak; Krzysztof Fujarewicz

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Feature selection based on logistic regression for 2-class classification of multidimensional molecular data

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2018) 11089 LNAI 286-290

DOI: 10.1007/978-3-319-99344-7_29

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Abstract

This paper describes a classification system which uses feature selection method based on logistic regression algorithm. As a feature elimination criterion the variance inflation factor of the statistical logistic regression model is used. The experimental results show that this method can be successfully applied for feature selection in classification problem of multidimensional microarray data.

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Student, S., Płuciennik, A., Jakubczak, M., & Fujarewicz, K. (2018). Feature selection based on logistic regression for 2-class classification of multidimensional molecular data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11089 LNAI, pp. 286–290). Springer Verlag. https://doi.org/10.1007/978-3-319-99344-7_29

Feature selection based on logistic regression for 2-class classification of multidimensional molecular data

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