| Procedure: Multi Objective Subspace Clustering algorithm |
| Begin |
| Apply preprocessing phase on data set D |
| = initial population of relevant subspaces /* Popsize = */ |
| While (the termination criterion is not satisfied) |
| for i = 1 to // for each individual in subspace |
| Randomly select chromosomes from the population |
| Call subspace_update ( ) |
| Compute objective functions for current chromosomes |
| Apply crossover operation with probability |
| Apply mutation operator with mutation probability |
| Compute objective functions for new offsprings |
| end for |
| end while |
| Select the best solution from population |
| End |
| Procedure subspace_update ( ) |
| Choose cluster centers {s = 1,…, from data set generated |
| by preprocessing phase |
| Repeat |
| Compute the membership matrix |
| for i =1 to do |
| for j = 1 to do // —number of cluster centers |
| if dist(, ) < dist(, ) then |
| = 0; |
| else |
| = 1; |
| end if |
| end for |
| end for |
| Compute the cluster center: |
| ; |
| Compute cluster weights encoded in each chromosome using |
| membership matrix and cluster center |
| until convergence |
