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# FAQ - PowerPoint PPT Presentation

FAQ. Olli Virmajoki. UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE JOENSUU, FINLAND. 11.12.2004. Merge Cost Equation. s i = i th cluster of data vertors s ij = cluster formed by merging i th and j th clusters n i = number of data vectors in s i

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Olli Virmajoki

UNIVERSITY OF JOENSUU

DEPARTMENT OF COMPUTER SCIENCE

JOENSUU, FINLAND

11.12.2004

• si = i th cluster of data vertors

• sij = cluster formed by merging i th and j th clusters

• ni = number of data vectors in si

• nij = numberof data vectors in sij

• = centroid (mean) of the data vectors in si

• = centroid (mean) of the data vectors in sij

• = average squared error between and the data vectors in si

• = average squared error between and the data vectors in sij

• = inner product of x and y

• max

• max

• max

• Data vectors xi in the cluster sa are divided into subclusters sa,j

• Removal is conseptually three step process: (1) remove the vectors from the current cluster sa (2) form the subclusters sa,j (3) merge the subclusters to the neighbor clusters sj

• The first term is the cost of the cluster before removal

• The second term is the sum of the cost values inside the subclusters

• The third term is the sum of the costs of merging the subclusters sa,jto their neighbor clusters sj

• M N iterations to cover the search space

• N distinct vertors to M non-distinct codewords lowers the search by M !

• Clusterings(N,M)

• Consider a number of vectors ordered into groups, one vector at a time

• Each vector in turn may:

• Either form a new group on its own, or

• Combine with other vectors already in a formed group.