Tabu Search :
Performs a search through the space of attribute subsets. Evading local maximums by accepting bad and diverse solutions and make further search in the best soluions. Stops when there's not more improvement in n iterations. For more information see:
Abdel-Rahman Hedar, Jue Wangy, Masao Fukushima (2006). Tabu Search for Attribute Reduction in Rough Set Theory.
The table below describes the options available for TabuSearch.
Set the probability of diversification. This is the probability of change of search subspace in an abrupt way
Set the number of attributes that are going to be in the initial Solution
Set the number of current solution's neighborhood to generate for looking for a better solution
Set the random seed.