Data Mining Utilizing Various Leveled Clustering Procedures on the Position of Workers in a Data Innovation Firm

Authors

Hussein Alkattan, Department of System Programming, South Ural State University, Chelyabinsk, RussiaFollow
Noor Razzaq Abbas, Al-Furat Al-Awsat Technical University, Najaf, Iraq.
Oluwaseun A. Adelaja, Information Communication and Technology Department, Lagos State University, Lagos, Nigeria.
Mostafa Abotaleb, Intelligent Systems and Machine Learning Lab, Shenzhen 518000, China.
Guma Ali, Department of Computer and Information Science, Muni University, Arua, Uganda.Follow

Document Type

Article

Keywords

Data Mining, Clustering Algorithm, Python, Clustering Analysis

Abstract

The reason of this paper is to clarify dynamic clustering, the divisive and agglomerative dynamic clustering techniques. It fundamentally centers on the concept of the divisive different leveled shapes as well known as the top-down approach by creating a workflow appear, dendrograms, clustered data table which accumulated the clusters based the chosen property, and appear the isolated between each cluster with the assistance of an data mining device called Python. The DIANA dynamic approach utilized data tests of the list of laborers in a Data Advancement firm to induce clusters from the position column inside the data test table. In this work, we in addition executed genuine infers by creating barchart that shows up the ages of the chosen agent sets plotted against the positions which are the Engineers, Assistants, Workers and Troughs.

How to Cite This Article

Alkattan, Hussein; Abbas, Noor Razzaq; Adelaja, Oluwaseun A.; Abotaleb, Mostafa; and Ali, Guma (2024) "Data Mining Utilizing Various Leveled Clustering Procedures on the Position of Workers in a Data Innovation Firm," Mesopotamian Journal of Computer Science: Vol. 4: Iss. 1, Article 7.
DOI: https://doi.org/10.58496/MJCSC/2024/008
Available at: https://map.researchcommons.org/mjcsc/vol4/iss1/7