Which of the following algorithms is commonly used for hierarchical clustering?Agglomerative clusteringExpectation-Maximization (EM)DBSCANK-Means
Question
Which of the following algorithms is commonly used for hierarchical clustering?Agglomerative clusteringExpectation-Maximization (EM)DBSCANK-Means
Solution
The algorithm commonly used for hierarchical clustering is Agglomerative clustering.
Here's a step-by-step explanation:
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Agglomerative clustering is a type of hierarchical clustering method. Hierarchical clustering, as the name suggests, creates a hierarchy of clusters.
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In Agglomerative clustering, each data point is initially considered as an individual cluster.
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Then, at each iteration, the two clusters that are the closest are combined together. This process is repeated until only a single cluster is left.
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The result is a tree-like diagram called a dendrogram, representing the nested grouping of patterns and similarity levels at each step of the clustering process.
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Other algorithms like Expectation-Maximization (EM), DBSCAN, and K-Means are not typically used for hierarchical clustering. EM is more associated with Gaussian mixture models, DBSCAN is a density-based clustering algorithm, and K-Means is a type of partitioning clustering.
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