MIP-BOOST: Efficient and Effective L0 Feature Selection for Linear Regression
نویسندگان
چکیده
منابع مشابه
Efficient Regularized Regression for Variable Selection with L0 Penalty
Variable (feature, gene, model, which we use interchangeably) selections for regression with high-dimensional BIGDATA have found many applications in bioinformatics, computational biology, image processing, and engineering. One appealing approach is the L0 regularized regression which penalizes the number of nonzero features in the model directly. L0 is known as the most essential sparsity meas...
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ژورنال
عنوان ژورنال: Journal of Computational and Graphical Statistics
سال: 2021
ISSN: 1061-8600,1537-2715
DOI: 10.1080/10618600.2020.1845184