Abstract
In this paper, we study the methods, techniques, and algorithms used in data mining, and from the studied algorithms, we emphasized the clustering algorithms, more precisely on the K-means algorithm. This algorithm was first studied using the Euclidean distance, then modifying the distance between the clusters using the distances Mahalanobis and Canberra. After implementing the algorithms in C/C++, we compared the clustering of the three algorithms, after which we modified them and studied the distance between the clusters.
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Ana-Maria Ramona, S., Marian Pompiliu, C., Stoyanova, M. (2020). Data Mining Algorithms for Knowledge Extraction. In: Fotea, S., Fotea, I., Văduva, S. (eds) Challenges and Opportunities to Develop Organizations Through Creativity, Technology and Ethics. GSMAC 2019. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-43449-6_20
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DOI: https://doi.org/10.1007/978-3-030-43449-6_20
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