LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) DAN ADAPTIVE RIDGE  (Least Absolute Shrinkage and Selection Operator (LASSO) and Adaptive Ridge)

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DC Field	Value	Language
dc.contributor.author	Yuliani Setia Dewi	-
dc.date.accessioned	2014-04-10T04:32:19Z	-
dc.date.available	2014-04-10T04:32:19Z	-
dc.date.issued	2014-04-10	-
dc.identifier.uri	http://repository.unej.ac.id/handle/123456789/56814	-
dc.description.abstract	The LASSO is a shrinkage and selection method for linear regression. It minimizes sum square of residual subject to sum of absolute coefficient less than a constant. Adaptive Ridge is special form of Ridge Regression, balancing the quadratic penalization on each parameter of the model. This paper describe the equivalence between LASSO (Least Absolute Shrinkage and Selection Operator) and Adaptive Ridge.	en_US
dc.language.iso	other	en_US
dc.relation.ispartofseries	Majalah Ilmiah Matematika dan Statistika;Volume 10, Juni 2010	-
dc.subject	LASSO, Ridge Regression, Adaptive Ridge, penalization	en_US
dc.title	LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) DAN ADAPTIVE RIDGE (Least Absolute Shrinkage and Selection Operator (LASSO) and Adaptive Ridge)	en_US
dc.type	Article	en_US
Appears in Collections:	Fakultas Matematika & Ilmu Pengetahuan Alam

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