A Practical Guide to Support Vector Classification
C. Hsu, C. Chang, und C. Lin. Department of Computer Science, National Taiwan University, (2003)
Zusammenfassung
Support vector machine (SVM) is a popular technique for classification. However, beginners who are not familiar with SVM often get unsatisfactory results since they miss some easy but significant steps. In this guide, we propose a simple procedure, which usually gives reasonable results.
%0 Report
%1 libsvmTutorial
%A Hsu, Chih-Wei
%A Chang, Chih-Chung
%A Lin, Chih-Jen
%D 2003
%K guide libsvm svm tutorial
%T A Practical Guide to Support Vector Classification
%U http://www.csie.ntu.edu.tw/~cjlin/papers.html
%X Support vector machine (SVM) is a popular technique for classification. However, beginners who are not familiar with SVM often get unsatisfactory results since they miss some easy but significant steps. In this guide, we propose a simple procedure, which usually gives reasonable results.
@techreport{libsvmTutorial,
abstract = {Support vector machine (SVM) is a popular technique for classification. However, beginners who are not familiar with SVM often get unsatisfactory results since they miss some easy but significant steps. In this guide, we propose a simple procedure, which usually gives reasonable results.},
added-at = {2008-05-28T19:14:22.000+0200},
author = {Hsu, Chih-Wei and Chang, Chih-Chung and Lin, Chih-Jen},
biburl = {https://www.bibsonomy.org/bibtex/2c04ef97dc3c3de168e684c3e4abe061b/jil},
institution = {Department of Computer Science, National Taiwan University},
interhash = {272d3522c22f3cf354b02c5ce6c4612a},
intrahash = {c04ef97dc3c3de168e684c3e4abe061b},
keywords = {guide libsvm svm tutorial},
timestamp = {2025-01-17T23:45:32.000+0100},
title = {A Practical Guide to Support Vector Classification},
url = {http://www.csie.ntu.edu.tw/~cjlin/papers.html},
year = 2003
}