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CVPR
2004
IEEE
14 years 9 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
ICMCS
2007
IEEE
133views Multimedia» more  ICMCS 2007»
14 years 1 months ago
Data Modeling Strategies for Imbalanced Learning in Visual Search
In this paper we examine a novel approach to the difficult problem of querying video databases using visual topics with few examples. Typically with visual topics, the examples a...
Jelena Tesic, Apostol Natsev, Lexing Xie, John R. ...
CSL
2006
Springer
13 years 7 months ago
A study in machine learning from imbalanced data for sentence boundary detection in speech
Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have const...
Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizab...
WWW
2008
ACM
14 years 8 months ago
Floatcascade learning for fast imbalanced web mining
This paper is concerned with the problem of Imbalanced Classification (IC) in web mining, which often arises on the web due to the "Matthew Effect". As web IC applicatio...
Xiaoxun Zhang, Xueying Wang, Honglei Guo, Zhili Gu...
JIFS
2008
155views more  JIFS 2008»
13 years 7 months ago
Improving supervised learning performance by using fuzzy clustering method to select training data
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
Donghai Guan, Weiwei Yuan, Young-Koo Lee, Andrey G...