Simulated Annealing Parameter Search¶
-
class
node_paramsearch.
ParameterSearch_SimulatedAnnealing
[source]¶ 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. This node should be considered _experimental_ and may change in the future
Configuration: cv
Number of fold in the default K-Fold cross validation. Ignored when cross-validation port is given
n_iter
Number of randomized searches done
cooling
Method for lowering temperature
cooling_arg
Argument A to cooling method. Exponential: T=A^t Linear ignores A Logarithmic: T=A/log(1+t)
Inputs: - in-model : model
in-model
- parameter space : table
param-space
- X : table
X
- Y : table
Y
- cross-validation : [(table,table)]
cross-validation
Outputs: - results : table
results
- parameters : table
parameters
- out-model : model
out-model