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.
Graph classification is important for different scientific applications; it can be exploited in various problems related to bioinformatics and cheminformatics. Given their graphs, there is increasing need for classifying small molecules to predict their properties such as activity, toxicity or mutagenicity. Using subtrees as feature set for graph classification in kernel methods has been shown to...
This paper addresses an important and vital problem within the general area of disease recognition, namely identifying disease biomarker genes. Given the complexity of this domain, the basic idea tacked in this paper is employing multiple agents to handle this problem. Though the developed methodology is general enough to be applied to any other domain, we concentrate on identifying cancer biomarkers...
In this paper, a new framework to build an adaptive classifier is introduced. At first, a clustering algorithm, density-based spatial clustering of applications with noise (DBSCAN) is applied to a set of sample data to form initial set of clusters. The clusters are represented as classes. Using support vector machine (SVM), a classifier model is generated. In real world application, data comes in...
In this paper, we present a multi-perspective representation (MPR) method, which takes advantage of the synergy of multiple representations of an information object. We have provided a detailed description of how to integrate the MPR scheme with support vector machines (MPR-SVM). The results of the experiments conducted on two benchmark data sets have shown the applicability and effectiveness of using...
In this paper, we try to identify a set of reduced features capable of distinguishing between two classes by performing double clustering using fuzzy c-means. We decided on using fuzzy c-means because a fuzzy model fits better the gene expression data analysis. Fuzziness parameter m is a major problem in applying fuzzy c- means method for clustering. In this approach, we applied fuzzy c-means clustering...
Extracting significant features from gene expression data is a hot subject that continues to receive great attention. Many methods have been proposed in the literature to deal with this issue, but all of these methods deal with features obtained directly from the data. Since microarray data exhibit a high degree of noise, in this paper we try to reduce the noise by using double clustering approach...
This paper proposes WaveQ, a content-based image retrieval system that classifies images as texture or non-texture, then uses a Daubechies wavelet decomposition to extract feature vector information from the images, and finally applies the OPTICS clustering algorithm to cluster the extracted data into groups of similar images. Queries are submitted to WaveQ in the form of an example image. WaveQ has...
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.