def inform(self):
    '\n          train the NN model\n        '
    speczs = self.training_data['redshift']
    print('stacking some data...')
    color_data = make_color_data(self.training_data)
    input_data = regularize_data(color_data)
    simplenn = sknn.MLPRegressor(hidden_layer_sizes=(12, 12), activation='tanh', solver='lbfgs')
    simplenn.fit(input_data, speczs)
    self.model = simplenn
train the NN model
def inform(self):
    '\n          \n        '
    speczs = self.training_data['redshift']
    print('stacking some data...')
    color_data = make_color_data(self.training_data)
    input_data = regularize_data(color_data)
    simplenn = sknn.MLPRegressor(hidden_layer_sizes=(12, 12), activation='tanh', solver='lbfgs')
    simplenn.fit(input_data, speczs)
    self.model = simplenn