CLUSTERING AND DATA MINING ON THE EXAMPLE OF HIV-INFECTED PEOPLE DATA


Kubegenova A.D. Zhakhiena A.G. Baigubenova S.K. Utyasheva G.S. Omarov A.N.
15 July 2022Little Lion Scientific

Journal of Theoretical and Applied Information Technology
2022#100Issue 135010 - 5018 pp.

The paper discusses aspects of data research, in-depth data analysis, knowledge acquisition, methods of data processing in the knowledge base, methods of intellectual analysis, and application of data mining in the field of medicine. A group of HIV-infected patients was identified, an analysis with a medical history was carried out, models and an algorithm of actions (input data) were developed, and analysis and experiments with data search methods were carried out. All diseases were presented as a set of numerical vectors and were grouped into clusters, according to the described methods, and with the help of this distribution, the Hopkins statistics value was calculated. Clustering itself was carried out using the usual tools of the sklearn library. Various methods of representation of multidimensional data in a two-dimensional plane are proposed, such as the method of basic components, the Kohonen line, etc. Two different clustering methods were considered, namely, the k-Medium method (using the Kmeans function from the Python sklearn library) and density-based clustering methods with autoconfiguration (from the HDBSCAN function from the Python Hdbscan library). In the case of comparison, the cluster structure is evaluated by changing various parameters of one algorithm (for example, the number of k groups); a model (or several) is built on the received and prepared objects, and its parameters are adjusted. After that testing and analysis of the results were carried out.

Clustering , Correlation , Manipulation , Sklearn , Vectorization

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Higher School Information Technologies, Kazakhstan Agrarian and Technical University named after Zhangir Khan, 51 Zhangir Khan str., Uralsk, 090009, Kazakhstan
Department of Engineering and Technology, The Faculty of Engineering and Humanities, West Kazakhstan Innovation and Technology University, 44/1 Ihsanov str., Uralsk, 090009, Kazakhstan

Higher School Information Technologies
Department of Engineering and Technology

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