def __init__(self, **kwargs): """ @param verbosity: Verbosity level @param mutationVariate: Variate used for mutation. Defaults to None @param mutation: Defaults to EvolinoSubMutation """ Filter.__init__(self) ap = KWArgsProcessor(self, kwargs) ap.add( 'verbosity', default=0 ) ap.add( 'mutationVariate', default=None ) ap.add( 'mutation', default=EvolinoSubMutation() ) if self.mutationVariate is not None: self.mutation.mutationVariate = self.mutationVariate
def __init__(self, evolino_network, dataset, **kwargs): """ @param evolino_network: an instance of NetworkWrapper() @param dataset: The evaluation dataset @param evalfunc: Compares output to target values and returns a scalar, denoting the fitness. Defaults to -mse(output, target). @param wtRatio: Float array of two values denoting the ratio between washout and training length. Defaults to [1,2] @param verbosity: Verbosity level. Defaults to 0 """ Filter.__init__(self) ap = KWArgsProcessor(self, kwargs) ap.add( 'verbosity', default=0 ) ap.add( 'evalfunc', default=lambda output, target: -Validator.MSE(output, target) ) ap.add( 'wtRatio', default=array([1,2], float) ) self.network = evolino_network self.dataset = dataset self.max_fitness = -Infinity
def __init__(self): Filter.__init__(self)
def __init__(self, **kwargs): """ @param **kwargs: will be forwarded to the EvolinoSubReproduction constructor """ Filter.__init__(self) self._kwargs = kwargs
def __init__(self): Filter.__init__(self) self.nParents = None self.sub_selection = EvolinoSubSelection()