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)
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

Ports:

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

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)
class node_paramsearch.ParameterSearch_SimulatedAnnealing[source]