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Spectral-Spatial-Aware Unsupervised Change Detection with Stochastic Distances and Support Vector Machines
(2021-04-01)
Change detection is a topic of great interest in remote sensing. A good similarity metric to compute the variations among the images is the key to high-quality change detection. However, most existing approaches rely on ...
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 ...
Advanced conjoint analysis using feature selection via support vector machines
(Elsevier, 2015)
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 ...
Automatic Feature Scaling and Selection for Support Vector Machine Classi cation with Functional Data
(Springer, 2020)
Functional Data Analysis (FDA) has become a very important eld
in recent years due to its wide range of applications. However, there are several
real-life applications in which hybrid functional data appear, i.e., data ...
Profit-based feature selection using support vector machines - General framework and an application for customer retention
(Elsevier, 2015)
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 ...
Obtaining Anti-Missile Decoy Launch Solution from a Ship Using Machine Learning Techniques
One of the most dangerous situations a warship may face is a missile attack launched from other ships, aircrafts, submarines or land. In addition, given the current scenario, it is not ruled out that a terrorist group may ...