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ESANN
2007
13 years 9 months ago
Classifying n-back EEG data using entropy and mutual information features
In this work we show that entropy (H) and mutual information (MI) can be used as methods for extracting spatially localized features for classification purposes. In order to incre...
Liang Wu, Predrag Neskovic, Etienne Reyes, Elena F...
CORR
2002
Springer
96views Education» more  CORR 2002»
13 years 7 months ago
Thumbs up? Sentiment Classification using Machine Learning Techniques
We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, w...
Bo Pang, Lillian Lee, Shivakumar Vaithyanathan
SDM
2008
SIAM
136views Data Mining» more  SDM 2008»
13 years 9 months ago
Exploration and Reduction of the Feature Space by Hierarchical Clustering
In this paper we propose and test the use of hierarchical clustering for feature selection. The clustering method is Ward's with a distance measure based on GoodmanKruskal ta...
Dino Ienco, Rosa Meo
SEBD
2008
169views Database» more  SEBD 2008»
13 years 9 months ago
Clustering the Feature Space
Abstract Dino Ienco and Rosa Meo Dipartimento di Informatica, Universit`a di Torino, Italy In this paper we propose and test the use of hierarchical clustering for feature selectio...
Dino Ienco, Rosa Meo
FLAIRS
2006
13 years 9 months ago
Evaluating WordNet Features in Text Classification Models
Incorporating semantic features from the WordNet lexical database is among one of the many approaches that have been tried to improve the predictive performance of text classifica...
Trevor N. Mansuy, Robert J. Hilderman