Measure the quality of clustering Dissimilarity/Similarity metric Similarity is expressed in terms of a distance function typically metric: d(,D The definitions of distance functions are usually rather different for interval-scaled boolean categorical ordinal ratio, and vector variables Weights should be associated with different variables based on applications and data semantics Quality of clustering There is usually a separate "quality function that measures the goodness" of a cluster It is hard to define similar enough"or "good enough The answer is typically highly subjectiveMeasure the Quality of Clustering ◼ Dissimilarity/Similarity metric ◼ Similarity is expressed in terms of a distance function, typically metric: d(i, j) ◼ The definitions of distance functions are usually rather different for interval-scaled, boolean, categorical, ordinal ratio, and vector variables ◼ Weights should be associated with different variables based on applications and data semantics ◼ Quality of clustering: ◼ There is usually a separate “quality” function that measures the “goodness” of a cluster. ◼ It is hard to define “similar enough” or “good enough” ◼ The answer is typically highly subjective 7