Clustering groups similar instances together from "summary" of Machine Learning by Ethem Alpaydin
Clustering is the process of grouping similar instances together based on some measure of similarity. The goal of clustering is to organize data into groups such that instances within the same group are more similar to each other than to those in other groups. This allows us to discover patterns and structures within the data that may not be immediately apparent. There are various clustering algorithms that can be used to achieve this goal. One common approach is the k-means algorithm, which partitions the data into k clusters by iteratively assigning instances to the cluster with the nearest mean. Another approach is hierarchical clustering, which builds a tree of clusters by successively merging the most similar clusters together. The choice of clustering algorithm and the number o...
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