Now showing items 1-10 of 386
Interactive Vector Field Feature Identification
(IEEE COMPUTER SOC, 2010)
We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features ...
Feature selection for Support Vector Machines via Mixed Integer Linear Programming
The performance of classification methods, such as Support Vector Machines, depends heavily on the proper choice of the feature set used to construct the classifier. Feature selection is an NP-hard problem that has been ...
Profit-based feature selection using support vector machines - General framework and an application for customer retention
Churn prediction is an important application of classification models that identify those customers most likely to attrite based on their respective characteristics described by e.g. socio-demographic and behavioral ...
Partially obscured human detection based on component detectors using multiple feature descriptors
This paper presents a human detection system based on component detector using multiple feature descriptors. The contribution presents two issues for dealing with the problem of partially obscured human. First, it presents ...
Advanced conjoint analysis using feature selection via support vector machines
One of the main tasks of conjoint analysis is to identify consumer preferences about potential products or services. Accordingly, different estimation methods have been proposed to determine the corresponding relevant ...
A WRAPPER METHOD FOR FEATURE SELECTION USING SUPPORT VECTOR MACHINES
(NORTH HOLLAND, 2009)
LINEAR PENALIZATION SUPPORT VECTOR MACHINES FOR FEATURE SELECTION
Sorting variables by using informative vectors as a strategy for feature selection in multivariate regression
(John Wiley & Sons LtdChichesterInglaterra, 2009)
Social-Spider Optimization-based Support Vector Machines applied for energy theft detection
(Elsevier B.V., 2016-01-01)
The problem of Support Vector Machines (SVM) tuning parameters (i.e., model selection) has been paramount in the last years, mainly because of the high computational burden for SVM training step. In this paper, we address ...
Exponential family Fisher vector for image classification
(Elsevier Science, 2015-07)
One of the fundamental problems in image classification is to devise models that allow us to relate the images to higher-level semantic concepts in an efficient and reliable way. A widely used approach consists on extracting ...