K-Means Clustering (Material from cs412, uiuc) - The Lack Thereof

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Comments on the K-Means Method

●

Strength: Relatively efficient: O(tkn), where n is # objects, k is # clusters, and t

is # iterations. Normally, k, t

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Comments on the K-Means Method ● Strength: Relatively efficient: O(tkn), where n is # objects, k is # clusters, and t is # iterations. Normally, k, t

Variations of the K-Means Method ● Most of the variants of the k-means which differ in ● ● ● Selection of the initial k means Dissimilarity calculations Strategies to calculate cluster means ● Handling categorical data: k-modes (Huang’98) ● ● ● ● Replacing means of clusters with modes Using new dissimilarity measures to deal with categorical objects Using a frequency-based method to update modes of clusters A mixture of categorical and numerical data: k-prototype method 5

Page 1 and 2: NARG! K-Means Clustering (Material
Page 3: The K-Means Clustering Method ● E

K-Means Clustering (Material from cs412, uiuc) - The Lack Thereof

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