Abstract:Logistic regression is a widely used statistical model to describe the relationship between a binary response variable and predictor variables in data sets. It is often used in machine learning to identify important predictor variables. This task, variable selection, typically amounts to fitting a logistic regression model regularized by a convex combination of ℓ 1 and ℓ 2 2 penalties. Since modern big data sets can contain hundreds of thousands to billions of predictor variables, variable selection methods de… Show more
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