Autor:	Price, Bradley S., Geyer, Charles J., Rothman, Adam J.
Rok vydání:	2013
Předmět:	Statistics - Machine Learning Computer Science - Learning Statistics - Computation
Druh dokumentu:	Working Paper
Popis:	We propose a penalized likelihood method to jointly estimate multiple precision matrices for use in quadratic discriminant analysis and model based clustering. A ridge penalty and a ridge fusion penalty are used to introduce shrinkage and promote similarity between precision matrix estimates. Block-wise coordinate descent is used for optimization, and validation likelihood is used for tuning parameter selection. Our method is applied in quadratic discriminant analysis and semi-supervised model based clustering. Comment: 24 pages and 9 tables, 3 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1310.3892 Zobrazit plný text záznamu View this record from Arxiv