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
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)