Operations research Solving support vector machine classification problems and their applications to supplier selection KANSAS STATE UNIVERSITY Chih-Hang Wu KimGitaeRecently, interdisciplinary (management, engineering, science, and economics) collaboration research has been growing to achieve the synergy and ...
Support vector regression (SVR) is a support vector machine for solving regression problems. 翻译结果3复制译文编辑译文朗读译文返回顶部 Support vector regression (SVR) is a support vector machine for solving regression problems. 翻译结果4复制译文编辑译文朗读译文返回顶部 ...
MODEL INDUCTION WITH SUPPORT VECTOR MACHINES: INTRODUCTIONS AND APPLICATIONS. Presents a study which investigated the possibility of using a machine learning paradigm based on the theory of statistical learning, namely that of the su... Dibike,Yonas,B.,... - 《Journal of Computing in Civil Engin...
Thus, the generalization ability of the fuzzy support vector machine is the same with or better than that of the support vector machine for pair- wise classification. We evaluate our method for four benchmark data sets and demonstrate the superiority of our method. 展开 ...
- 2008 () Citation Context ...o solve this problem, conventional tools are used, for instance, the Naive Bayes and Support Vector Machine classifiers [... GR Xue,D Xing,Q Yang,... - International Acm Sigir Conference on Research & Development in Information Retrieval 被引量: 255发表: 200...
Particle Swarm Optimization with Support Vector Machine for Optimization Problems with Implicit Constraints SAWAFUCHI Tetsuo , AIYOSHI Eitaro 電気学会研究会資料. IIC, 産業計測制御研究会 2007(1), 81-84, 2007-03-05关键词: particle swarm optimization support vector machine implicit constraints discrimina...
2022, Lecture Notes on Data Engineering and Communications Technologies Predicting Resilient Modulus of Cementitiously Stabilized Subgrade Soils Using Neural Network, Support Vector Machine, and Gaussian Process Regression 2021, International Journal of Geomechanics View all citing articles on ScopusView...
In this paper we present a new fuzzy classification method based on Support Vector Machine (SVM) to treat multi-class problems. Generally, SVMs classifiers are designed to solve binary classification problem. In order to handle multi-class classification problem, we present a new method to build ...
However, implementing a support vector machine is quite complex and difficult. James McCaffrey presents a complete working example of an SVM that will help you gain a good understanding of exactly how SVMs work and help you be able to use a library implementation....
Sequential Minimal Optimization (SMO) is one of simple but fast iterative algorithm for Support Vector Machine (SVM), while there is a large amount of vect... X Yang,H Guan,F Tang,... - Fifth International Conference on Innovative Mobile & Internet Services in Ubiquitous Computing 被引量: ...