Distributed Information Systems (CSCI 5533) Presentation ID: 19

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Presentation transcript:

Distributed Information Systems (CSCI 5533) Presentation ID: 19 Clustering Algorithm Submitted to: Dr. Liaw, Morris Submitted by: Kumar, Manoj

Algorithm 5.3 BEA Input: AA : attribute affinity matrix Output: CA : clustered affinity matrix Begin { initialize; AA is an nxn matrix} CA(*,1)← AA(*,1) CA(*,2)← AA(*,2) index ← 3 while index ≤ n do {choose the “best” location for attribute AAindex }

begin for i from 1 to index – 1 by 1 do calculate cont (Ai-1, Aindex, Ai) end-for calculate cont (Aindex-1, Aindex, Aindex+1) loc ← placement given by maximum cont value For j from index to loc by -1 do CA(*,j)← CA(*,j-1)

CA(*,loc)← AA(*,index) index ← index + 1 end-while Order the rows according to the relative ordering of columns end. {BEA}

AM= =

bond(Ax,Ay) = AM= A1 A2 ……. Ai-1 Ai Aj Aj+1…….. An AM’ AM’’

AMold = AM’ + AM’’ + bond(Ai-1,Ai) +. bond(Ai,Aj) +bond(Aj,Ai) + AMold = AM’ + AM’’ + bond(Ai-1,Ai) + bond(Ai,Aj) +bond(Aj,Ai) + bond(Aj,Aj+1) = + + 2bond(Ai,Aj)

AMnew = AM’ + AM’’ + bond(Ai,Ak) + bond(Ak,Ai) + bond(Ak,Aj) + bond(Aj,Ak) AMnew = AM’ + AM’’ + 2bond(Ai,Ak) + 2bond(Ak,Aj) Cont(Ai,Ak,Aj) = AMnew – Amold = 2bond(Ai,Ak) + 2bond(Ak,Aj) - 2bond(Ai,Aj)

Questions ??