| 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 |
