Univerza na Primorskem Fakulteta za matematiko, naravoslovje in informacijske tehnologije
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petek, 11. september 2020 Jamolbek MATTIEV: Distance based Clustering of Class Association Rules to Build a Compact, Accurate and Descriptive Classifier

V ponedeljek, 14. septembra 2020, bo ob 16.00 uri prek spletnih orodij na daljavo izvedeno predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.

ČAS/PROSTOR: 14. september 2020 ob 16.00 na daljavo

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PREDAVATELJ: Jamolbek MATTIEV
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Jamolbek Mattiev has a Master degree in Computer Science from National University of Uzbekistan. He was awarded with first degree diploma at “the best Master Dissertation Work of Uzbekistan” competition in his master studies. He is a Teaching Assistant at the University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies and he is final year PhD student at the Department of Information Sciences and Technologies.

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NASLOV: Distance based Clustering of Class Association Rules to Build a Compact, Accurate and Descriptive Classifier
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POVZETEK:

In this research work, we propose new methods that are able to reduce the number of class association rules produced by “classical” class association rule classifiers, while maintaining an accurate classification model that is comparable to the ones generated by state-of-the-art classification algorithms. More precisely, we propose new associative classifiers, called DC, DDC and CDC, that use distance-based agglomerative hierarchical clustering as a post-processing step to reduce the number of its rules, and in the rule-selection step, we use different strategies (based on database coverage and cluster centers) for each algorithm.

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Predavanje bo potekalo v angleškem jeziku prek spletnega orodja Zoom.
Do predavanja dostopate tako, da se povežete prek sledeče povezave:

https://us02web.zoom.us/j/297328207

Vabljeni!