Open AccessPENENTUAN MODEL TERBAIK REGRESI RIDGE DAN TERAPANNYA
Author(s) -
Sri Utami Zuliana
Publication year - 2018
Publication title -
jurnal ilmiah matematika dan pendidikan matematika (jmp)/jurnal ilmiah matematika dan pendidikan matematika
Language(s) - English
Resource type - Journals
eISSN - 2550-0422
pISSN - 2085-1456
DOI - 10.20884/1.jmp.2018.10.2.2843
Subject(s) - multicollinearity , ridge , regression , computer science , regression analysis , elastic net regularization , variance (accounting) , convergence (economics) , variance inflation factor , statistics , linear regression , mathematics , geography , economics , cartography , accounting , economic growth
Ridge regression is one of penalized regression methods. Penalized regression methods are usually used for solving the problem of multicollinearity. The best model in ridge regression has been chosen by some previous techniques. In the techniques there is bias-variance trade-off. In this paper, Schall algorithm will be applied for choosing the best model. Schall algorithm is faster because it only needs a few iteratives to be convergence.