Simulated Annealing Parameter Search¶
Hyperparameter search by simulated annealing.
Documentation¶
Uses simulated annealing to find the optimal parameters by considering a hyper cube of all possible indices to the given parameter table. Each column of the parameter table corresponds to one axis of this cube with a range corresponding to the non-masked rows of the parameter table. The radius for the annealing process assumes that all axes have unit length regardless of the number of non-masked rows. Note: This node should be considered _experimental_ and may change in the future.
Definition¶
Input ports¶
- in-model
Type: modelDescription: in-model- parameter space
Type: tableDescription: param-space- X
Type: tableDescription: X- Y
Type: tableDescription: Y- cross-validation
Type: [(table,table)]Description: cross-validationOptional number of ports: 0–1 (default: 0)
Output ports¶
- results
Type: tableDescription: results- parameters
Type: tableDescription: parameters- out-model
Type: modelDescription: out-model
Configuration¶
- Cooling method (cooling)
Method for lowering temperature
- Cooling argument (cooling_arg)
Argument A to cooling method. Exponential: T=A^t Linear ignores A Logarithmic: T=A/log(1+t)
- Cross validation splits (cv)
Number of fold in the default K-Fold cross validation. Ignored when cross-validation port is given
- iterations (n_iter)
Number of randomized searches done
Implementation¶
- class node_paramsearch.ParameterSearch_SimulatedAnnealing[source]