# How should the hyper parameters be defined for the other algorithms defined for sklearn_crfsuite.CRF

In the example given for sklearn_crfsuite, the parameter space that needs to be passed to a cross_validating class like RandomizedSearchCV is defined as below.

params_space = {
'c1': scipy.stats.expon(scale=0.5),
'c2': scipy.stats.expon(scale=0.05),
}


In the example the algorithm that is shown is "lbfgs". Other supported algorithms in sklearn_crfsuite are "l2sgd", "ap", "pa", "arow". How should the variable params_space be defined in those cases?

C1 and C2 are coefficients for L1 and L2 regularization, respectively. You can use the same definition of params_space regardless of the optimization algorithm.