def _initialize_weights(self):
        w1 = self._init_weights(shape=self.n_hidden * (self.n_features + 1),
                                zero_init_weight=self.zero_init_weight,
                                seed=self.random_seed)
        w1 = w1.reshape(self.n_hidden, self.n_features + 1)
        w2 = self._init_weights(shape=self.n_output * (self.n_hidden + 1),
                                zero_init_weight=self.zero_init_weight,
                                seed=self.random_seed)
        w2 = w2.reshape(self.n_output, self.n_hidden + 1)
        return w1, w2
Initialize weights with small random numbers.
dataset/ETHPy150Open rasbt/mlxtend/mlxtend/classifier/neuralnet_mlp.py/NeuralNetMLP._initialize_weights