Работы, цитирующие эту работу

Работ: 4

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

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

   Jamolbek Mattiev, Monte Davityan, Branko Kavšek

   СтатьяData Mining Algorithms and ApplicationsMathematics2023Цитирований: 1

   ABIABI:AkademIndex/openalex/2023.article.001595

2. ACHC: Associative Classifier Based on Hierarchical Clustering

   Jamolbek Mattiev, Branko Kavšek

   ГлаваData Mining Algorithms and ApplicationsLecture notes in computer science2021Цитирований: 0

   ABIABI:AkademIndex/openalex/2021.chapter.000095

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

   Jamolbek Mattiev, Christopher Meza, Branko Kavšek

   СтатьяData Mining Algorithms and ApplicationsApplied Sciences2022Цитирований: 0

   ABIABI:AkademIndex/openalex/2022.article.002421

4. Importance of Data Preprocessing for Accurate and Effective Prediction of Breast Cancer: Evaluation of Model Performance in Novel Data

   Vekani Baloyi, Jamolbek Mattiev, Sello Mokwena

   СтатьяAI in cancer detectionBig Data and Cognitive Computing2025Цитирований: 0

   ABIABI:AkademIndex/openalex/2025.article.002448