COMPARATIVE ANALYSIS OF K-MEANS AND FUZZY C-MEANS ALGORITHMS ON DEMOGRAPHIC DATA USING THE PCA METHOD
Eltun Ahmadov · Problems of Information Technology · 2023
The concept of demography, which includes the processes such as birth, death, natural increase, improvement of employment and standard of living of the population, migration, etc., occupies a unique place in the global processes of the modern era. In this regard, this article uses clustering algorithms, which are estimated as a demographic data mining technology. For the analysis of demographic data, experiments are performed using k-means and fuzzy c-means clustering algorithms in the Python programming language. The experiment uses PCA method to reduce the dimension and get more effective results. Silhouette, Calinski-Harabasz and Davies-Bouldin indices, and CPU time are used to evaluate the quality of the algorithm. The result of the experiment shows the possibility of achieving an effective result through the k-means and fuzzy c-means clustering algorithms by applying the PCA method in the demographic data analysis.