learner.exhaustive – Exhaustive learners

This modules provides exhaustive learners. Currently, it include the ListLearner class which scores a list of networks. In the future, we might implent exhaustive learners that score all possible networks meeting some constraints (as defined by prior models).

Configuration Parameters

listlearner.networks

List of networks to score. default=

ListLearner Class

class pebl.learner.exhaustive.ListLearner(data_=None, prior_=None, networks=None)

Create a ListLearner learner.

networks should be a list of networks (as network.Network instances).

split(count)

Split the learner into multiple learners.

Splits self.networks into count parts. This is similar to MPI’s scatter functionality.