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Etsuo Miyaoka

Tokyo University of Science



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Asanao Shimokawa

Tokyo University of Science



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256 – Contributed Poster Presentations: Section on Statistical Learning and Data Science

On the Selection of Regression Model Using Machine Learning

Sponsor: Section on Statistical Learning and Data Science
Keywords: Genetic algorithm, Logistic regression, Model selection

Etsuo Miyaoka

Tokyo University of Science

Asanao Shimokawa

Tokyo University of Science

In this study, we focus on the model selection problem in the logistic regression model. When construct the model from a data set, we need to decide which covariates should be included in the model. In addition to this, it is also need to consider interactions between covariates and their nonlinear transformations. In order to perform these operations automatically, we examine the automatic model selection method using a geneti algorithm. We propose the algorithm for this purpose and verify its performance through simulation studies.

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