A modified k-means clustering algorithm with Mahalanobis distance for clustering incomplete data sets

Cluster analysis is an art of finding grounds in data in such a way that objects in the same group are similar to each other, whereas objects in different groups are as dissimilar as possible. The most commonly used clustering algorithm is the K-means with Euclidean distance. However, such distance...

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Bibliografiska uppgifter
Huvudupphovsman: Moreno, Iresh Granada
Materialtyp: Lärdomsprov
Språk:engelska
Publicerad: 2009
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