Add to ORKGAbstract:- This paper presents a genetic algorithm (GA) methodology for training a support vector machine (SVM). The SVM method may be viewed as a quadratic optimization problem with linear constraints, where the objective is to minimize the error learning rate and the Vapnik-Chervonenkis (VC) dimension in order to get an Optimal Separating Hyperplane (OSH) that classifies two sets of data. A SVM is a very good tool for classification problems which displays an excellent generalization ability. In order to test our method we solve the XOR problem, a canonical nonlinearly separable problem. We used a genetic algorithm (GA) called Vasconcelos ’ GA (VGA). The genome was selected to solve the dual SVM problem, where each individual corresponds ...
Abstract—The use of support vector machine (SVM) for function approximation has increased over the p...
The aims of the paper are multifold, to propose a new method to determine a suitable value of the bi...
Abstract—The use of support vector machine (SVM) for function approximation has increased over the p...
The Support Vector Machine method has a good learning and generalization ability. Unfortunately, the...
The purpose of the paper is to apply a nonlinear programming algorithm for com-puting kernel and rel...
Support vector machines are relatively new approach for creating classifiers that have become increa...
99學年度林慧珍教師升等代表著作[[abstract]]Being a universal learning machine, a support vector machine (SVM) suffe...
The problem of feature selection is a difficult combinatorial task in Machine Learning and of high p...
The problem of feature selection is a difficult combinatorial task in Machine Learning and of high p...
The problem of feature selection is a difficult combinatorial task in machine learning and of high p...
Support vector machines (SVMs) were originally formulated for the solution of binary classification ...
Support vector machines (SVMs) were originally formulated for the solution of binary classification ...
In this paper we demonstrate that it is possible to gradually improve the performance of support vec...
A classical algorithm in classification is the support vector machine (SVM) algorithm. Based on Vapn...
Parameters of support vector machines (SVM) which is optimized by standard genetic algorithm is easy...
Abstract—The use of support vector machine (SVM) for function approximation has increased over the p...
The aims of the paper are multifold, to propose a new method to determine a suitable value of the bi...
Abstract—The use of support vector machine (SVM) for function approximation has increased over the p...
The Support Vector Machine method has a good learning and generalization ability. Unfortunately, the...
The purpose of the paper is to apply a nonlinear programming algorithm for com-puting kernel and rel...
Support vector machines are relatively new approach for creating classifiers that have become increa...
99學年度林慧珍教師升等代表著作[[abstract]]Being a universal learning machine, a support vector machine (SVM) suffe...
The problem of feature selection is a difficult combinatorial task in Machine Learning and of high p...
The problem of feature selection is a difficult combinatorial task in Machine Learning and of high p...
The problem of feature selection is a difficult combinatorial task in machine learning and of high p...
Support vector machines (SVMs) were originally formulated for the solution of binary classification ...
Support vector machines (SVMs) were originally formulated for the solution of binary classification ...
In this paper we demonstrate that it is possible to gradually improve the performance of support vec...
A classical algorithm in classification is the support vector machine (SVM) algorithm. Based on Vapn...
Parameters of support vector machines (SVM) which is optimized by standard genetic algorithm is easy...
Abstract—The use of support vector machine (SVM) for function approximation has increased over the p...
The aims of the paper are multifold, to propose a new method to determine a suitable value of the bi...
Abstract—The use of support vector machine (SVM) for function approximation has increased over the p...