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106
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ISDA
2009
IEEE
15 years 8 months ago
Clustering-Based Feature Selection in Semi-supervised Problems
— In this contribution a feature selection method in semi-supervised problems is proposed. This method selects variables using a feature clustering strategy, using a combination ...
Ianisse Quinzán, José Manuel Sotoca,...
WILF
2007
Springer
171views Fuzzy Logic» more  WILF 2007»
15 years 8 months ago
Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps
Abstract. Analysis and visualization of high-dimensional clinical proteomic spectra obtained from mass spectrometric measurements is a complicated issue. We present a wavelet based...
Frank-Michael Schleif, Thomas Villmann, Barbara Ha...
ICASSP
2009
IEEE
15 years 6 months ago
Learning to maximize signal-to-noise ratio for reverberant speech segregation
Monaural speech segregation in reverberant environments is a very difficult problem. We develop a supervised learning approach by proposing an objective function that directly rel...
Zhaozhang Jin, DeLiang Wang
ICML
1997
IEEE
15 years 5 months ago
Efficient Feature Selection in Conceptual Clustering
Feature selection has proven to be a valuable technique in supervised learning for improving predictive accuracy while reducing the number of attributes considered in a task. We i...
Mark Devaney, Ashwin Ram
95
Voted
AAAI
2006
15 years 3 months ago
Kernel Methods for Word Sense Disambiguation and Acronym Expansion
The scarcity of manually labeled data for supervised machine learning methods presents a significant limitation on their ability to acquire knowledge. The use of kernels in Suppor...
Mahesh Joshi, Ted Pedersen, Richard Maclin, Sergue...