The lecturer at the University of Information Technology and Communications (UoITC), Sudair Sadiq Abdel -Jabbar, published a joint scientific research with researchers from sober Iraqi universities in the international journal, “Journal of Engineering and Technology for Industrial Applications (Jetia)”, which is classified within the prestigious Scopus global base.
This achievement is the culmination of the efforts of joint scientific cooperation between the university and Iraqi scientific research institutions, in an effort to enhance the position of Iraqi scientific research on the global academic map.
The research was entitled “The Effect of Data Conversion Methods (Naive Bayes, C5.0 & Support Vector Machine) on the Performance of Classification Algorithms in Data Mining”.
The study focuses on the field of classification, which is one of the basic technologies in data mining and artificial intelligence (AI), as the research team compared the performance of three leading classification algorithms:

1. Naive Bayes: it is a simple and effective statistical method that relies on the theory of Bayes, and assumes the independence of the features.
2. “C5.0” : which represents a development of Decision Tree Algorithms, and is characterized by its efficiency in dealing with complex data.
3. Support Vector Machines – SVM: it is one of the powerful algorithms that work to find the best separation limit for data categories.

The comparison aimed to measure the effect of the different data conversion methods on the accuracy and efficiency of the performance of these algorithms, which contributes to provide valuable guidelines for researchers and specialists to choose best practices to improve the results of their projects in the fields of computing and artificial intelligence.