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
Documentation
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-modelmodel
in-model
- parameter spacetable
param-space
- Xtable
X
- Ytable
Y
- cross-validation[(table,table)]
cross-validation
- Output ports:
- resultstable
results
- parameterstable
parameters
- out-modelmodel
out-model
Definition
Input ports
- in-model
model
in-model
- parameter space
table
param-space
- X
table
X
- Y
table
Y
- cross-validation
0 - 1, [(table,table)]
cross-validation
Output ports
- results
table
results
- parameters
table
parameters
- out-model
model
out-model
