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Clustering the Various Categorical Data: An Exploration of Algorithms and Performance Analysis

Publication Type : Conference Paper

Publisher : IEEE

Source : 2023 4th International Conference for Emerging Technology, INCET 2023, 2023

Url : https://ieeexplore.ieee.org/document/10170508

Campus : Bengaluru

School : School of Engineering

Department : Electrical and Electronics

Year : 2023

Abstract : Clustering is a method of grouping data based on similarities, and is an unsupervised technique for discovering patterns in data. In this research paper, various clustering algorithms such as k-Means, DBSCAN, Spectral Clustering, Gaussian Mixture, and Agglomerative Clustering are compared and evaluated on Amazon Prime Video Movies and TV Shows, Netflix Movies and TV Shows, and Disney+ Movies and Tv Shows datasets. The results of the study indicate that the k-Means algorithm performed well in clustering the data for all datasets, with an overall high level of performance. Additionally, the study provides valuable insights into the genre distribution of the data, and highlights the advantages and limitations of each clustering algorithm.

Cite this Research Publication : Kumar, R., Pati, P.B., Deepa, K., Yanan, S., "Clustering the Various Categorical Data: An Exploration of Algorithms and Performance Analysis", 2023 4th International Conference for Emerging Technology, INCET 2023, 2023

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