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Correspondingly, the DIANA algorithm can help teachers understand students' learning situations based on students' learning data, provide students with personalized subject tutoring, and help students overcome learning difficulties. With such academic data, it is only a matter of time that students' academic performance improves and teachers' teaching quality improves. Summary and explosion, data has become an indispensable part of our lives and work. We need more effective methods to process massive
amounts of data, especially in the field of AI. Artificial intelligence Malaysia Phone Number Data algorithms can not only improve our work efficiency, but also help us make more accurate decisions. This article focuses on the K-means clustering algorithm and hierarchical clustering algorithm among the clustering algorithms. We start from the basic concepts, talk about the steps of algorithm implementation, bring the algorithm into the actual scene through hypothetical cases, and pull the algorithm from the book into the real world to see what problems the algorithm can help us solve.
example, the K-means clustering algorithm can divide customers into different groups, which can help companies better understand customers and formulate more effective marketing strategies. The AGNES algorithm in the hierarchical clustering algorithm can group similar documents into one category, helping enterprises better manage and analyze documents. The DIANA algorithm can complete academic analysis and help schools or educational institutions better understand students' learning situations and formulate more effective teaching
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