Regularized margin-based conditional log-likelihood loss for prototype learning

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 模式分析与学习

	Regularized margin-based conditional log-likelihood loss for prototype learning
	Jin, Xiao-Bo; Liu, Cheng-Lin; Hou, Xinwen
发表期刊	PATTERN RECOGNITION
	2010-07-01
卷号	43 期号:7 页码:2428-2438
文章类型	Article
摘要	The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithm. The minimum classification error (MCE) method and the soft nearest prototype classifier (SNPC) method are two important algorithms using misclassification loss. This paper proposes a new prototype learning algorithm based on the conditional log-likelihood loss (CLL), which is based on the discriminative model called log-likelihood of margin (LOGM). A regularization term is added to avoid over-fitting in training as well as to maximize the hypothesis margin. The CLL in the LOGM algorithm is a convex function of margin, and so, shows better convergence than the MCE. In addition, we show the effects of distance metric learning with both prototype-dependent weighting and prototype-independent weighting. Our empirical study on the benchmark datasets demonstrates that the LOGM algorithm yields higher classification accuracies than the MCE, generalized learning vector quantization (GLVQ), soft nearest prototype classifier (SNPC) and the robust soft learning vector quantization (RSLVQ), and moreover, the LOGM with prototype-dependent weighting achieves comparable accuracies to the support vector machine (SVM) classifier. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.
关键词	Prototype Learning Conditional Log-likelihood Loss Log-likelihood Of Margin (Logm) Regularization Distance Metric Learning
WOS标题词	Science & Technology ; Technology
关键词[WOS]	VECTOR QUANTIZATION ; TEXT CATEGORIZATION ; NETWORK CLASSIFIERS ; CLASSIFICATION ; ALGORITHMS ; RECOGNITION ; LVQ
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000277475100007
引用统计	被引频次：52[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3065
专题	多模态人工智能系统全国重点实验室_模式分析与学习
作者单位	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Jin, Xiao-Bo,Liu, Cheng-Lin,Hou, Xinwen. Regularized margin-based conditional log-likelihood loss for prototype learning[J]. PATTERN RECOGNITION,2010,43(7):2428-2438.
APA	Jin, Xiao-Bo,Liu, Cheng-Lin,&Hou, Xinwen.(2010).Regularized margin-based conditional log-likelihood loss for prototype learning.PATTERN RECOGNITION,43(7),2428-2438.
MLA	Jin, Xiao-Bo,et al."Regularized margin-based conditional log-likelihood loss for prototype learning".PATTERN RECOGNITION 43.7(2010):2428-2438.