ann_best_number_hidden2.py

import sklearn.neural_network
import numpy
import matplotlib.pyplot

input_data = numpy.array([[5, 1.5],
                          [4, 2.5],
                          [1.5, 2],
                          [2.5, 0.5],
                          [6, 1],
                          [3.5, 2],
                          [3, 1.5],
                          [3, 1]])
output_data = numpy.array([0, 0, 0, 0, 1, 1, 1, 1])

my_neural_network = sklearn.neural_network.MLPClassifier(hidden_layer_sizes=(4,2), max_iter=1000)

my_neural_network.fit(X=input_data, y=output_data)
print("Weights:", my_neural_network.coefs_)
print("Bias:", my_neural_network.intercepts_)

labels = my_neural_network.predict(X=input_data)
print("Predicted Labels:", labels)