Simulated Annealing Parameter Search

../../../../_images/annealing_hyperparam.svg

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)

Input ports:
in-model : model
in-model
parameter space : table
param-space
X : table
X
Y : table
Y
cross-validation : [(table,table)]
cross-validation
Output ports:
results : table
results
parameters : table
parameters
out-model : model
out-model
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
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)
class node_paramsearch.ParameterSearch_SimulatedAnnealing[source]