A review of support vector machines with respect to spatial data
A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples.
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my.utm.253732017-08-06T03:20:35Z http://eprints.utm.my/id/eprint/25373/ A review of support vector machines with respect to spatial data Kohram, Mojtaba Md. Sap, Mohd. Noor QA75 Electronic computers. Computer science A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples. 2007 Conference or Workshop Item PeerReviewed Kohram, Mojtaba and Md. Sap, Mohd. Noor (2007) A review of support vector machines with respect to spatial data. In: Postgraduate Annual Research Seminar (PARS’ 07), 2007, UTM, Johor Bahru. |
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QA75 Electronic computers. Computer science Kohram, Mojtaba Md. Sap, Mohd. Noor A review of support vector machines with respect to spatial data |
description |
A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples. |
format |
Conference or Workshop Item |
author |
Kohram, Mojtaba Md. Sap, Mohd. Noor |
author_facet |
Kohram, Mojtaba Md. Sap, Mohd. Noor |
author_sort |
Kohram, Mojtaba |
title |
A review of support vector machines with respect to spatial data |
title_short |
A review of support vector machines with respect to spatial data |
title_full |
A review of support vector machines with respect to spatial data |
title_fullStr |
A review of support vector machines with respect to spatial data |
title_full_unstemmed |
A review of support vector machines with respect to spatial data |
title_sort |
review of support vector machines with respect to spatial data |
publishDate |
2007 |
url |
http://eprints.utm.my/id/eprint/25373/ |
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1643647576279351296 |
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13.18916 |