예제 #1
0
    def __init__(self, hidden_layer_sizes=(100,), activation="relu", solver='adam', alpha=0.0001, batch_size='auto',
                 learning_rate="constant", learning_rate_init=0.001, power_t=0.5, max_iter=200, shuffle=True,
                 random_state=None, tol=1e-4, verbose=False, warm_start=False, momentum=0.9, nesterovs_momentum=True,
                 early_stopping=False, validation_fraction=0.1, beta_1=0.9, beta_2=0.999, epsilon=1e-8):
        warnings.filterwarnings(module='sklearn*', action='ignore', category=ConvergenceWarning)

        BaseWrapperClf.__init__(self)
        _skMLPClassifier.__init__(
            self, hidden_layer_sizes, activation, solver, alpha, batch_size, learning_rate, learning_rate_init, power_t,
            max_iter, shuffle, random_state, tol, verbose, warm_start, momentum, nesterovs_momentum, early_stopping,
            validation_fraction, beta_1, beta_2, epsilon)
    def __init__(self, variables = None, arquitecture = None):
        v = variables if variables else select_variables()
        a = arquitecture if arquitecture else select_arquitecture()

        self.variables = Variable(v)
        self.arquitecture = Arquitecture(a)

        self.accuracy = 0

        self.fitness = 0 # fitness = accuracy
        self.genes = (self.variables.raw(), self.arquitecture.raw())

        # MLP Classifier init
        # http://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html
        MLPClassifier.__init__(
            self,
            hidden_layer_sizes = tuple(self.arquitecture.raw()),
            learning_rate = 'constant',
            learning_rate_init = 0.001,
            max_iter = 3000
        )
 def __init__(self, k=1000):
     if k != None:
         MutableMLPClassifier.K_features = k
     MLPClassifier.__init__(self,hidden_layer_sizes=150, activation='logistic', solver='adam')