Multiobjective Subset Selection (NSGA-II)

This node finds (near)optimal fixed-sized subsets of rows based one one or more criteria. It uses the NSGA-II algorithm to find an approximation of the set of non-dominated solutions, i.e. the Pareto front .
In the dialogue you can choose which column from the input table should be optimized in which way. Each column represents an objective which - together with a function on that column, like sum of all values in the selected set or average distance of all values - can either be minimized or maximized. By default each objective is maximized , thus if you want to minimize negate the objective.
The node runs until a certain number of individuals have been evaluated. You can also stop the search manually in the node's view.

Input ports

1. Type: Table
   Any datatable
   Datatable with all rows to choose from during evaluating subsets

Output ports

1. Type: Table
   Solutions as table
   A list of non-dominated solutions found during the search, together with their objective values and the rows from the input table that are contained in the solution.
2. Type: Table
   Hypervolume statistics
   This table contains the evolution of the hypervolume of the Pareto front.
3. Type: Rowset Filter
   Solution model
   A list of non-dominated solutions found during the search, together with their objective values and the rows from the input table that are contained in the solution. This model can be used with the Rowset Filter node to filter out certain rows from the input table.