aima/learning.py
def WeightedLearner(unweighted_learner):
    """Given a learner that takes just an unweighted dataset, return
    one that takes also a weight for each example. [p. 749 footnote 14]"""
    def train(dataset, weights):
        return unweighted_learner(replicated_dataset(dataset, weights))
    return train
def WeightedLearner(unweighted_learner):
    """Given a learner that takes just an unweighted dataset, return
    one that takes also a weight for each example. [p. 749 footnote 14]"""
    def train(dataset, weights):
        return unweighted_learner(replicated_dataset(dataset, weights))
    return train
def WeightedLearner ( unweighted_learner ) : def train ( dataset , weights ) : return unweighted_learner ( replicated_dataset ( dataset , weights ) ) return train
Given a learner that takes just an unweighted dataset, return
    one that takes also a weight for each example. [p. 749 footnote 14]
Given a learner that takes just an unweighted dataset return one that takes also a weight for each example . [ p . 749 footnote 14 ]