Pendugaan Parameter Regresi Logistik Dengan Jaringan Syaraf  Tiruan

dc.contributor.author	Djuraidah, Anik
dc.date.accessioned	2012-04-09T02:23:04Z
dc.date.available	2012-04-09T02:23:04Z
dc.date.issued	2007
dc.identifier.issn	1978-4538
dc.identifier.uri	http://repository.ipb.ac.id/handle/123456789/54057
dc.description.abstract	Logistic regression can be mapped equivalent to artificial neural network (ANN) without hidden layer with logistic as activation junction, hence logistic regression is subset of ANN The result study on binary and poly-chotolnous response data show that parameter estimation values of ANN and logistic regression are similar. In comparison with ANN. logistic regression has standard procedure for estimation and testing parameter.	en
dc.publisher	Jurusan Pendidikan Matematika FMIFA UNY
dc.relation.ispartofseries	Volume 3,Nomor 1, Juni;
dc.subject	logistic regression	en
dc.subject	generalized linear model	en
dc.subject	artificial neural network	en
dc.subject	activation function	en
dc.subject	hidden layer	en
dc.title	Pendugaan Parameter Regresi Logistik Dengan Jaringan Syaraf Tiruan	en
dc.type	Article	en