A practical guide to support vector classification
Date Issued
2003
Date
2003
Author(s)
DOI
2006092712291477314
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.
Publisher
臺北市:國立臺灣大學資訊工程學系
Type
other
File(s)![Thumbnail Image]()
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Name
guide.pdf
Size
167.35 KB
Format
Adobe PDF
Checksum
(MD5):70509c1a6346ab6da25035053b5367aa
