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<title>Advanced Reasoning Group</title>
<link>http://hdl.handle.net/2160/20</link>
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<pubDate>Wed, 19 Jun 2013 00:21:10 GMT</pubDate>
<dc:date>2013-06-19T00:21:10Z</dc:date>
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<title>Assisting Failure Modes and Effects Analysis of a System</title>
<link>http://hdl.handle.net/2160/13968</link>
<description>Assisting Failure Modes and Effects Analysis of a System
International PCT Application
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<pubDate>Thu, 16 Dec 2010 00:00:00 GMT</pubDate>
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<dc:date>2010-12-16T00:00:00Z</dc:date>
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<title>Fuzzy-rough data mining</title>
<link>http://hdl.handle.net/2160/13828</link>
<description>Fuzzy-rough data mining
Jensen, Richard
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<pubDate>Sat, 31 Dec 2011 00:00:00 GMT</pubDate>
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<dc:date>2011-12-31T00:00:00Z</dc:date>
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<title>Rough Sets and Current Trends in Computing : 7th International Conference, RSCTC 2010, Warsaw, Poland, June 28-30,2010. Proceedings</title>
<link>http://hdl.handle.net/2160/13418</link>
<description>Rough Sets and Current Trends in Computing : 7th International Conference, RSCTC 2010, Warsaw, Poland, June 28-30,2010. Proceedings
Szczuka, Marcin; Kryszkiewicz, Marzena; Ramanna, Sheela; Jensen, Ricahrd; Hu, Qinghua
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<pubDate>Fri, 01 Jan 2010 00:00:00 GMT</pubDate>
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<dc:date>2010-01-01T00:00:00Z</dc:date>
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<title>Fuzzy Rough Positive Region based Nearest Neighbour Classification</title>
<link>http://hdl.handle.net/2160/13116</link>
<description>Fuzzy Rough Positive Region based Nearest Neighbour Classification
Verbiest, Nele; Cornelis, Chris; Jensen, Richard
This paper proposes a classifier that uses fuzzy rough set theory to improve the Fuzzy Nearest Neighbour (FNN) classifier. We show that previous attempts to use fuzzy rough set theory to improve the FNN algorithm have some shortcomings and we overcome them by using the fuzzy positive region to measure the quality of the nearest neighbours in the FNN classifier. A preliminary experimental evaluation shows that the new approach generally improves upon existing methods.
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<pubDate>Sun, 01 Jan 2012 00:00:00 GMT</pubDate>
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<dc:date>2012-01-01T00:00:00Z</dc:date>
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