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ESWA
2007
146views more  ESWA 2007»
15 years 4 months ago
A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy
Two parameters, C and r, must be carefully predetermined in establishing an efficient support vector machine (SVM) model. Therefore, the purpose of this study is to develop a gene...
Chih-Hung Wu, Gwo-Hshiung Tzeng, Yeong-Jia Goo, We...
TSP
2008
180views more  TSP 2008»
15 years 4 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
INFORMS
2010
177views more  INFORMS 2010»
15 years 2 months ago
Binarized Support Vector Machines
The widely used Support Vector Machine (SVM) method has shown to yield very good results in Supervised Classification problems. Other methods such as Classification Trees have bec...
Emilio Carrizosa, Belen Martin-Barragan, Dolores R...
KAIS
2010
144views more  KAIS 2010»
15 years 2 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
ICDAR
2009
IEEE
15 years 2 months ago
Lexicon-Based Word Recognition Using Support Vector Machine and Hidden Markov Model
Hybrid of Neural Network (NN) and Hidden Markov Model (HMM) has been popular in word recognition, taking advantage of NN discriminative property and HMM representational capabilit...
Abdul Rahim Ahmad, Christian Viard-Gaudin, Marzuki...