This paper describes an e-mail spam filter based on local SVM, namely on the SVM classifier trained only on a neighborhood of the message to be classified, and not on the whole training data available. Two problems are stated and solved. First, the selection of the right size of neighborhood is shown to be critical; our solution is based on the estimation of the a-posteriori probability of the ...

This paper is an overview of a recent approach for solving linear support vector machines (SVMs), the PEGASOS algorithm. The algorithm is based on a technique called the stochastic subgradient descent and employs it for solving the optimization problem posed by the soft margin SVM a very popular classifier. We briefly introduce the SVM problem and one of the widely used solvers, SVM light, then...

In this paper, we first introduce some facts about semi-supervised learning and its often used methods such as generative mixture models, self-training, co-training and Transductive SVM and so on. Then we present a self-training semi-supervised SVM algorithm based on which we give out a modified algorithm. In order to demonstrate its validity and effectiveness, we carry out some experiments whi...

The standard -norm SVM is known for its good performance in twoclass classification. In this paper, we consider the -norm SVM. We argue that the -norm SVM may have some advantage over the standard -norm SVM, especially when there are redundant noise features. We also propose an efficient algorithm that computes the whole solution path of the -norm SVM, hence facilitates adaptive selection of th...

In the field of medicine, with the introduction of computer systems that can collect and analyze massive amounts of data, many non-invasive diagnostic methods are being developed for a variety of conditions. In this study, our aim is to develop a non-invasive method of classifying respiratory sounds that are recorded by an electronic stethoscope and the audio recording software that uses variou...

internet applications spreading and its high usage popularity result insignificant increasing of cyber-attacks. consequently, network security has becomea matter of importance and several methods have been developed for these attacks.for this purpose, intrusion detection systems (ids) are being used to monitor theattacks occurred on computer networks. data mining techniques, machinelearning, ne...

The standard 2-norm SVM is known for its good performance in twoclass classi£cation. In this paper, we consider the 1-norm SVM. We argue that the 1-norm SVM may have some advantage over the standard 2-norm SVM, especially when there are redundant noise features. We also propose an ef£cient algorithm that computes the whole solution path of the 1-norm SVM, hence facilitates adaptive selection of...