Ushbu ishga iqtibos qilgan ishlar

5 ta ish

Ish: A comparative study of clustering methods

1. Distance based clustering of class association rules to build a compact, accurate and descriptive classifier

   Jamolbek Mattiev, Branko Kavšek

   MaqolaData Mining Algorithms and ApplicationsComputer Science and Information Systems20204 iqtibos

   ABIABI:AkademIndex/openalex/2026.other.416363

2. CMAC: Clustering Class Association Rules to Form a Compact and Meaningful Associative Classifier

   Jamolbek Mattiev, Branko Kavšek

   BobData Mining Algorithms and ApplicationsLecture notes in computer science20203 iqtibos

   ABIABI:AkademIndex/openalex/2026.other.468606

3. ACMKC: A Compact Associative Classification Model Using K-Modes Clustering with Rule Representations by Coverage

   Jamolbek Mattiev, Monte Davityan, Branko Kavšek

   MaqolaData Mining Algorithms and ApplicationsMathematics20231 iqtibos

   ABIABI:AkademIndex/openalex/2023.article.001595

4. ACHC: Associative Classifier Based on Hierarchical Clustering

   Jamolbek Mattiev, Branko Kavšek

   BobData Mining Algorithms and ApplicationsLecture notes in computer science20210 iqtibos

   ABIABI:AkademIndex/openalex/2021.chapter.000095

5. The Effect of “Directness” of the Distance Metric to Produce Compact and Accurate Associative Classification Models

   Jamolbek Mattiev, Christopher Meza, Branko Kavšek

   MaqolaData Mining Algorithms and ApplicationsApplied Sciences20220 iqtibos

   ABIABI:AkademIndex/openalex/2022.article.002421