Parameter Optimization Loop Start
This loop starts a parameter optimization loop. In the dialog you can enter several parameters with an interval and a step size. The loop will vary these parameters following a certain search strategy. Each parameter is output as a flow variable. The parameters can the be used inside the loop body either directly or by converting them with a Variable to Table node into a data table.
Currently three search strategies are available:
- Brute Force: All possible parameter combination (given the intervals and the step sizes) are checked and the best is returned.
- Hillclimbing: A random start combination is created and the direct neighbors (respecting the given intervals and step sizes) are evaluated. The best combination among the neighbors is the start point for the next iteration. If no neighbor improves the objective function the loop terminates.
- Random Search: Parameter combinations are randomly chosen and evaluated. The specified start and stop values define the parameter space from which is randomly drawn. Optionally, there can also a step size be defined to restrict the possible parameter values. The loop terminates after a specified number of iterations or, if early stopping is activated, when for a specified number of rounds the objective value has not improved. Note, that it is drawn with replacement. While duplicate parameter combinations will be processed just once, each of them still count as an iteration. Due to that, it may happen that actually less loop iterations are processed than defined.
- Type: Flowvariable A parameter combination as flow variables
Analytics > Mining > Optimization
Make sure to have this extension installed:
KNIME Optimization extension
Update site for KNIME Analytics Platform 3.7:
KNIME Analytics Platform 3.7 Update Site