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ICML
2004
IEEE
15 years 6 months ago
Gradient LASSO for feature selection
LASSO (Least Absolute Shrinkage and Selection Operator) is a useful tool to achieve the shrinkage and variable selection simultaneously. Since LASSO uses the L1 penalty, the optim...
Yongdai Kim, Jinseog Kim
167
Voted
CATA
2009
15 years 2 months ago
Nearest Shrunken Centroid as Feature Selection of Microarray Data
The nearest shrunken centroid classifier uses shrunken centroids as prototypes for each class and test samples are classified to belong to the class whose shrunken centroid is nea...
Myungsook Klassen, Nyunsu Kim
ICMCS
2005
IEEE
145views Multimedia» more  ICMCS 2005»
15 years 6 months ago
From Physiological Signals to Emotions: Implementing and Comparing Selected Methods for Feature Extraction and Classification
Little attention has been paid so far to physiological signals for emotion recognition compared to audio-visual emotion channels, such as facial expressions or speech. In this pap...
Johannes Wagner, Jonghwa Kim, Elisabeth Andr&eacut...
81
Voted
ESANN
2008
15 years 2 months ago
Classification of chestnuts with feature selection by noise resilient classifiers
In this paper we solve the problem of classifying chestnut plants according to their place of origin. We compare the results obtained by state of the art classifiers, among which,...
Elena Roglia, Rossella Cancelliere, Rosa Meo
130
Voted
MIR
2010
ACM
217views Multimedia» more  MIR 2010»
15 years 6 months ago
Feature selection for content-based, time-varying musical emotion regression
In developing automated systems to recognize the emotional content of music, we are faced with a problem spanning two disparate domains: the space of human emotions and the acoust...
Erik M. Schmidt, Douglas Turnbull, Youngmoo E. Kim