«data description»
۱۵۱٬۶۲۰ نتیجهPredicting drug protein interactions based on improved support vector data description in unbalanced data
Introduction: Predicting drug-protein interactions is critical in drug discovery, but traditional laboratory methods are expensive and time-consuming. Computational approaches, especially those leveraging machine learning, are increasingly popular. This paper introduces VASVDD, a
Deep Dual Support Vector Data description for anomaly detection on attributed networks
Networks are ubiquitous in the real world such as social networks and communication networks, anomaly detection on aims at finding nodes whose structural or attributed patterns deviate significantly from majority of reference nodes. However, most traditional methods neglect relat
A procedure using support vector data description and mutual information for end price assessment in online C2C auction
We propose a systematic procedure for assessing the end price of an item in a C-to-C auction site. These sites deal with used product and the product features vary substantially even within a single product category that makes price assessment difficult. Besides, the true market
Feature scaling in support vector data description
When in a classification problem only samples of one class are easily accessible, this problem is called a one-class classification problem. Many standard classifiers, like backpropagation neural networks, fail on this data. Some other classifiers, like k-means clustering or near
Online SVM learning: from classification to data description and back
The paper presents two useful extensions of the incremental SVM in the context of online learning. An online support vector data description algorithm enables application of the online paradigm to unsupervised learning. Furthermore, online learning can be used in the large-scale
Incremental Learning Algorithm for Support Vector Data Description
Support vector data description (SVDD) has become a very attractive kernel method due to its good results in many novelty detection problems.Training SVDD involves solving a constrained convex quadratic programming,which requires large memory and enormous amounts of training time
A support vector data description approach to target detection in hyperspectral imagery
Spectral variability remains a challenging problem for target detection and classification in hyperspectral imagery (HSI). In this paper, we have applied the nonlinear support vector data description (SVDD) to perform full-pixel target detection. Using a pure target signature, we
A Novel Incipient Fault Detection and Diagnosis Scheme Based on Kernel Density Weighting Support Vector Data Description: Application on the DAMADICS Benchmark Process
Support vector data description (SVDD) is a classical process monitoring skill and usually uses Euclidean distance to evaluate the status of process. It should be noted that proposed evaluation method restricts detection performance for some faults, when overall fault has structu
Dealing with Imbalanced Dataset Leveraging Boundary Samples Discovered by Support Vector Data Description
These days, imbalanced datasets, denoted throughout the paper by ID, (a dataset that contains some (usually two) classes where one considerably smaller number of samples than other(s)) emerge in many real world problems (like health care systems or disease diagnosis systems, anom
A hidden process regression model for functional data description. Application to curve discrimination
A new approach for functional data description is proposed in this paper. It consists of a regression model with a discrete hidden logistic process which is adapted for modeling curves with abrupt or smooth regime changes. The model parameters are estimated in a maximum likelihoo