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 ...
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...
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...
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 ...
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...