On the generalization ability of GRLVQ networks

被引：44

作者：

Hammer, B ^{[1
]}

Strickert, M

Villmann, T

机构：

[1] Univ Osnabruck, Dept Math Comp Sci, LNM, D-4500 Osnabruck, Germany

[2] Univ Leipzig, Clin Psychotherapy, Leipzig, Germany

来源：

NEURAL PROCESSING LETTERS | 2005年 / 21卷 / 02期

关键词：

adaptive metric; generalization bounds; LVQ; margin optimization; relevance LVQ;

D O I：

10.1007/s11063-004-1547-1

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We derive a generalization bound for prototype-based classifiers with adaptive metric. The bound depends on the margin of the classifier and is independent of the dimensionality of the data. It holds for classifiers based on the Euclidean metric extended by adaptive relevance terms. In particular, the result holds for relevance learning vector quantization (RLVQ) [4] and generalized relevance learning vector quantization (GRLVQ) [19].

引用

页码：109 / 120

页数：12

共 50 条

[41] The Impact of Enriching Electroencephalogram in Spatial Metadata on Interpretability and Generalization Ability of Graph Neural Networks
L. S. Sidorov
A. I. Maysuradze
Pattern Recognition and Image Analysis, 2024, 34 (4) : 1255 - 1263
[42] Improving the Generalization Ability of Deep Neural Networks for Cross-Domain Visual Recognition
Zheng, Jianwei
Lu, Chao
Hao, Cong
Chen, Deming
Guo, Donghui
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS, 2021, 13 (03) : 607 - 620
[43] A new method to improve the generalization ability of neural networks: A case study of nuclear mass training
Zhao, Tianliang
Zhang, Hongfei
NUCLEAR PHYSICS A, 2022, 1021
[44] Mining and Injecting Legal Prior Knowledge to Improve the Generalization Ability of Neural Networks in Chinese Judgments
Chen, Yaying
Ma, Ji
Gu, Nanfei
Wang, Xintong
He, Minghua
ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, ICANN 2023, PT V, 2023, 14258 : 350 - 362
[45] Leveraging the Generalization Ability of Deep Convolutional Neural Networks for Improving Classifiers for Color Fundus Photographs
Son, Jaemin
Kim, Jaeyoung
Kong, Seo Taek
Jung, Kyu-Hwan
APPLIED SCIENCES-BASEL, 2021, 11 (02): : 1 - 10
[46] Fault Diagnosis Using Neural Networks for Parallel Shaft Gearboxes and Discussion on Its Generalization Ability
Liu, Zhanchi
Sun, Heqing
PROCEEDINGS OF 2020 IEEE 9TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE (DDCLS'20), 2020, : 1288 - 1292
[47] REIN: A Robust Training Method for Enhancing Generalization Ability of Neural Networks in Autonomous Driving Systems
Yu, Fuxun
Liu, Chenchen
Chen, Xian
24TH ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE (ASP-DAC 2019), 2019, : 456 - 461
[48] GENERALIZATION ABILITY OF PERCEPTRONS WITH CONTINUOUS OUTPUTS
BOS, S
KINZEL, W
OPPER, M
PHYSICAL REVIEW E, 1993, 47 (02): : 1384 - 1391
[49] THE EFFECTS OF LESIONS ON THE GENERALIZATION ABILITY OF A PERCEPTRON
BARBATO, DML
FONTANARI, JF
JOURNAL OF PHYSICS A-MATHEMATICAL AND GENERAL, 1993, 26 (08): : 1847 - 1863
[50] ON THE GENERALIZATION ABILITY OF DISTRIBUTED ONLINE LEARNERS
Towfic, Zaid J.
Chen, Jianshu
Sayed, Ali H.
2012 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP), 2012,

← 1 2 3 4 5 →