Combining Supervised and Unsupervised Learning for GIS Classification
Combining Supervised and Unsupervised Learning for GIS Classification
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Contents
This paper presents a new hybrid learning algorithm for unsupervised classification tasks. We combined Fuzzy c-means learning algorithm and a supervised version of Minimerror to develop a hybrid incremental strategy allowing unsupervised classifications. We applied this new approach to a real-world database in order to know if the information conta...
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Full title
Combining Supervised and Unsupervised Learning for GIS Classification
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TN_cdi_proquest_journals_2087650395
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2087650395
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E-ISSN
2331-8422
