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» Unsupervised Feature Selection Using Feature Similarity
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BMCBI
2004
181views more  BMCBI 2004»
13 years 8 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
SAC
2005
ACM
14 years 2 months ago
A hierarchical naive Bayes mixture model for name disambiguation in author citations
Because of name variations, an author may have multiple names and multiple authors may share the same name. Such name ambiguity affects the performance of document retrieval, web ...
Hui Han, Wei Xu, Hongyuan Zha, C. Lee Giles
ICASSP
2008
IEEE
14 years 3 months ago
Hybrid feature selection for gesture recognition using support vector machines
This paper presents an approach for a multi-cue based two-dimensional gesture recognition that combines two different forms of cues, namely shape cues and motion cues, in a suppor...
Yu Yuan, Kenneth Barner
EMNLP
2009
13 years 6 months ago
Classifier Combination for Contextual Idiom Detection Without Labelled Data
We propose a novel unsupervised approach for distinguishing literal and non-literal use of idiomatic expressions. Our model combines an unsupervised and a supervised classifier. T...
Linlin Li, Caroline Sporleder
SBBD
2000
168views Database» more  SBBD 2000»
13 years 10 months ago
Fast Feature Selection Using Fractal Dimension
Dimensionalitycurse and dimensionalityreduction are two issues that have retained highinterest for data mining, machine learning, multimedia indexing, and clustering. We present a...
Caetano Traina Jr., Agma J. M. Traina, Leejay Wu, ...