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» A Hierarchical Classifier Using New Support Vector Machine
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AI
2011
Springer
12 years 11 months ago
Using a Heterogeneous Dataset for Emotion Analysis in Text
In this paper, we adopt a supervised machine learning approach to recognize six basic emotions (anger, disgust, fear, happiness, sadness and surprise) using a heterogeneous emotion...
Soumaya Chaffar, Diana Inkpen
TSP
2008
180views more  TSP 2008»
13 years 7 months ago
Support Vector Machine Training for Improved Hidden Markov Modeling
We present a discriminative training algorithm, that uses support vector machines (SVMs), to improve the classification of discrete and continuous output probability hidden Markov ...
Alba Sloin, David Burshtein
SCAI
2008
13 years 9 months ago
Defect Prediction in Hot Strip Rolling Using ANN and SVM
One of the largest factors affecting the loss for steel manufacturing are defects in the steel strips produced. Therefore the prediction of these defects forehand would be very im...
Manu Hietaniemi, Ulla Elsilä, Perttu Laurinen...
GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
13 years 11 months ago
Evolving kernels for support vector machine classification
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
Keith Sullivan, Sean Luke
PRL
2006
79views more  PRL 2006»
13 years 7 months ago
Multi-class feature selection for texture classification
In this paper, a multi-class feature selection scheme based on recursive feature elimination (RFE) is proposed for texture classifications. The feature selection scheme is perform...
Xue-wen Chen, Xiang-Yan Zeng, Deborah van Alphen