Sparse multinomial logistic regression: fast algorithms and generalization bounds
نویسندگان
چکیده
منابع مشابه
Multinomial logistic regression
Multinomial logistic regression is the extension for the (binary) logistic regression when the categorical dependent outcome has more than two levels. For example, instead of predicting only dead or alive, we may have three groups, namely: dead, lost to follow-up, and alive. In the analysis to follow, a reference group has to be chosen for comparison, the appropriate group would be the alive, i...
متن کاملExtreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification
A Fast and Robust Framework for Hyperspectral Image Classification Faxian Cao1, Zhijing Yang1*, Jinchang Ren2, Wing-Kuen Ling1 1 School of Information Engineering, Guangdong University of Technology, Guangzhou, 510006, China; [email protected]; [email protected]; [email protected] 2 Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, G1 1XW, UK; jinchan...
متن کاملMultinomial Logistic Regression Ensembles
This article proposes a method for multiclass classification problems using ensembles of multinomial logistic regression models. A multinomial logit model is used as a base classifier in ensembles from random partitions of predictors. The multinomial logit model can be applied to each mutually exclusive subset of the feature space without variable selection. By combining multiple models the pro...
متن کاملSparse Multinomial Logistic Regression via Bayesian L1 Regularisation
Multinomial logistic regression provides the standard penalised maximumlikelihood solution to multi-class pattern recognition problems. More recently, the development of sparse multinomial logistic regression models has found application in text processing and microarray classification, where explicit identification of the most informative features is of value. In this paper, we propose a spars...
متن کاملHyperspectral Image Classification Based on a Fast Bregman Sparse Multinomial Logistic Regression Algorithm
The Sparse Multinomial Logistic Regression (SMLR) method introduced in (Krishnapuram, 2005) is among the state-of-the-art in supervised learning. However its application to large datasets, such as hyperspectral imagery is still a rather challenging task from the computational point of view, sometimes even impossible to perform. In this paper, the Bregman iteration-based SMLR method (Bregman-SML...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 2005
ISSN: 0162-8828,2160-9292
DOI: 10.1109/tpami.2005.127