Input: A 2D-matrix A with m rows and n columns. Two parameters k1 and
k2, where k1 and k2 are both positive integers.
Output: (k1 × k2) co-clusters of the matrix A, where k1 is the number of
partitions of the m rows and k2 is the number of partitions of the n columns.
Main Variables:
A non-negative integer k as the loop counter;
A k1 × k2 matrix X with each entry a real number as the artificial central
point of one of the k1 ∗ k2 co-clusters of the matrix A;
A m × k1 matrix Y1 as the row assignment matrix with {0, 1} as the value of
each entry; and
A n × k2 matrix Y2 as the column assignment matrix with {0, 1} as the value
of each entry.
begin
0 (Initialization). Set the loop counter k := 0. Randomly set the initial
values of the three matrices X^k, Y1^k(y1 power k) and Y2^k(y2 power k not 2^k) and compute the initial
objective value v0 := max − ∥A − X ×1(this is x1) Y1(this y 1) ×2(this is x2) Y2∥F.
1 (Block Improvement). 1.1 Based on the values in matrices X^k and Y^k1 , get the optimal column assignment matrix Y ′ 2 and compute the objective value vY2 := max−||A−Xk ×1 Y k 1 ×2 Y ′ 2||F;
1.2 Based on the values in matrices X^k and Y2 ^k(y2 power k) , get the optimal row assignment matrix Y ′ 1 and compute the objective value vY1 := max−||A−Xk ×1 Y ′ 1 ×2 Y k 2||F;
1.3 Based on the values in matrices Y k 1 and Y k 2 , get the optimal matrix X′ and compute the objective value vX := max−||A−X′×1 Y k 1 ×2 Y k 2||F.
2 (Maximum Improvement). vk+1 := max{vY2,vY1,vx};
If vk+1 = vY2 then update Y2: X^k+1 = X^k, Y^ k+1 1 = Y ^k 1 , and Y^ k+1 2 = Y ′ 2;
If vk+1 = vY1 then update Y1: X^k+1 = X^k, Y^ k+1 1 = Y ′ 1, and Y^ k+1 2 = Y ^k 2 ;
If vk+1 = vX then update X: X^k+1 = X′, Y^ k+1 1 = Y^ k 1 , and Y^ k+1 2 = Y ^k 2 ;
3 (Stopping Criterion). If |vk+1 − vk| < ϵ, go to Step 4. Otherwise, set k := k + 1, and go to Step 1. 4 (Outputting Co-clusters). According to the assignment matrices Y 1^ k+1,Y 2^ k+1, print the k1 ×k2 co-clusters of A.
end
I ATTACHED THE FILE ALGORITHM TO BE IMPLEMENTED.
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