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.
- Type: TableAny datatableDatatable with all rows to choose from during evaluating subsets