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Clustering - Coggle Diagram
Clustering
Hierarchical
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Builds hierarchy of clusters where each node is a cluster consisting of the clusters of its daughter nodes
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K-means
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Disadvantages
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Potentially returns different clusters each time it is run due to random initialization of centroids
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Different Types
Partitioning-based
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e.g. K-means, k-median, etc.
Hierarchical
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e.g. Agglomerative, Divisive
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What
Cluster = group of objects that are similar to other objects in the cluster and dissimilar to data points in other clusters
