Simulated Annealing Parameter Search¶
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
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- 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
- 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)