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» On Combining Classifiers
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PREMI
2007
Springer
14 years 3 months ago
Ensemble Approaches of Support Vector Machines for Multiclass Classification
Support vector machine (SVM) which was originally designed for binary classification has achieved superior performance in various classification problems. In order to extend it to ...
Jun-Ki Min, Jin-Hyuk Hong, Sung-Bae Cho
ICDAR
1999
IEEE
14 years 1 months ago
Cursive Character Detection using Incremental Learning
This paper describes a new hybrid architecture for an artificial neural network classifier that enables incremental learning. The learning algorithm of the proposed architecture d...
Jean-François Hébert, Marc Parizeau,...
AMT
2006
Springer
147views Multimedia» more  AMT 2006»
14 years 20 days ago
Semi-Supervised Text Classification Using Positive and Unlabeled Data
Text classification using positive and unlabeled data refers to the problem of building text classifier using positive documents (P) of one class and unlabeled documents (U) of man...
Shuang Yu, Xueyuan Zhou, Chunping Li
EVOW
2006
Springer
14 years 17 days ago
A Hybrid GA/SVM Approach for Gene Selection and Classification of Microarray Data
We propose a Genetic Algorithm (GA) approach combined with Support Vector Machines (SVM) for the classification of high dimensional Microarray data. This approach is associated to ...
Edmundo Bonilla Huerta, Béatrice Duval, Jin...
FLAIRS
2006
13 years 10 months ago
Using Validation Sets to Avoid Overfitting in AdaBoost
AdaBoost is a well known, effective technique for increasing the accuracy of learning algorithms. However, it has the potential to overfit the training set because its objective i...
Tom Bylander, Lisa Tate