Border sampling techniques in Machine Learning
Border identification (BI), which is regarded as a sample selection technique in Machine Learning, was previously proposed to help learning systems focus on the most relevant portion of the training set so as to improve learning accuracy. However, the traditional BI implementation suffers from a ser...
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| Format: | Others |
| Language: | en |
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University of Ottawa (Canada)
2013
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| Online Access: | http://hdl.handle.net/10393/30010 http://dx.doi.org/10.20381/ruor-20031 |