Data mining
PyIT-MLFS: a Python-based information theoretical multi-label feature selection library

Sadegh Eskandari

Volume 11, Issue 1 , March 2022, , Pages 9-15

http://dx.doi.org/10.22105/riej.2022.308916.1252

Abstract
  Multi-label learning is an emerging research direction that deals with data in which an instance may belong to multiple class labels simultaneously. As many multi-label data contain very large feature space with hundreds of irrelevant andredundant features, multi-label feature selection is a fundamental ...  Read More

Data mining
Customer segmentation to identify key customers based on RFM model by using data mining techniques

Abdolmajid Imani; Meysam Abbasi; Farahnaz Ahang; Hassan Ghaffari; Mohamad Mehdi

Volume 11, Issue 1 , March 2022, , Pages 62-76

http://dx.doi.org/10.22105/riej.2021.291738.1229

Abstract
  Accurate identification, attracting, and keeping the customers particularly loyal Customer Relationship Management (CRM) with the goal of optimum allotment of resources and achievement to higher profit is not a competitive profit, but it is a life persistence necessity of companies in virtual space. ...  Read More

Data mining
Data mining and diagnosis of heart diseases: a hybrid approach to the b-mine algorithm and association rules

Shookoofa Mostofi; Sohrab Kordrostami; Amir Hossein Refahi; Marzieh Faridi Masooleh; Soheil Shokri

Volume 11, Issue 1 , March 2022, , Pages 77-91

http://dx.doi.org/10.22105/riej.2022.302672.1243

Abstract
  Existing systems for diagnosing heart disease are time consuming, expensive, and prone to error. In this regard, a diagnostic algorithm has been proposed for the causes of heart disease based on a frequent pattern with the B-mine algorithm optimized by association rules. Initially, a data set of disease ...  Read More