COFADMM: A Computational Features Selection with Alternating Direction Method of Multipliers
نویسندگان
چکیده
منابع مشابه
COFADMM: A Computational Features Selection with Alternating Direction Method of Multipliers
Due to the explosion in size and complexity of Big Data, it is increasingly important to be able to solve problems with very large number of features. Classical feature selection procedures involves combinatorial optimization, with computational time increasing exponentially with the number of features. During the last decade, penalized regression has emerged as an attractive alternative for re...
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ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2014
ISSN: 1877-0509
DOI: 10.1016/j.procs.2014.05.074