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What is Data Mining in Banking Sector Analysis about?

This document discusses applications of data mining techniques in the banking sector. It begins with an introduction to how data mining can help banks with customer relationship management, retention, and fraud detection. It then describes common supervised and unsupervised data mining algorithms and their functions, including decision trees, naive Bayes, k-means clustering, and apriori association rule mining. The document aims to analyze how these techniques can be applied in banking for tasks like credit

Author

Anonymous DLEF3Gv

Language

EN