The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Due to the complexity of the underlying biological processes, gene expression data obtained from DNA microarray technologies are typically noisy and have very high dimensionality and these make the mining of such data for gene function prediction very difficult. To tackle these difficulties, we propose to use an incremental fuzzy mining technique called incremental fuzzy mining (IFM). By transforming...
The intrusion detection system (IDS) deals with huge amount of data which contains irrelevant and redundant features causing slow training and testing process, higher resource consumption as well as poor detection rate. To overcome these limitations, we introduce the concept of lightweight IDS. The lightweight IDSs are small, powerful, and flexible enough to be used as permanent elements of the network...
Intrusion Detection Systems (IDSs) deal with large amount of data containing irrelevant and redundant features, which leads to slow training and testing processes, heavy computational resources and low detection accuracy. Therefore, the features selection is an important issue in intrusion detection. Reducing the features set improves the system accuracy and speeds up the training and testing phases...
In this paper a new fuzzy linear support vector machine formulation for regression problems is proposed and solved by the active set computational strategy. In this model, to each input data a fuzzy membership value is associated so that the input data can contribute proportionally to the learning of the decision surface. The proposed method has the advantage that its solution is obtained by solving...
The fuzzy support vector machines (FSVMs) can be used to deal with multiclass classification problems where the key issue is to solve a quadratic programming problem. This paper introduces a new fuzzy multiclass support vector machines (FMSVMs) based on compact description of data, which extends the exiting support vector machine method to the case of k-class problem in one optimization task (quadratic...
A hybrid fuzzy-SVM classifier, used to automate leukaemia diagnosis based on microarray gene expression data, is presented. A publicly available dataset was used to develop and test the classifier. A fuzzy gene filter was developed to select the genes which show significant class variation between various leukaemia types. The results obtained from using all the genes for classification is compared...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.