def main():
size_of_learn_sample = int(len(x) * 0.9)
print(size_of_learn_sample)
NN = NeuralNetwork(x, y, 0.5)
# NN.print_matrices()
NN.train()
NN.print_matrices()
ground_truth_dataset = [
[15, 3, 1],
[10, 5, 1],
[20, 1, 1],
[1, 5, 0],
[5, 0, 0],
[30, 0, 1],
[2, 1, 0],
[5, 5, 1],
[7, 10, 0],
[25, 6, 1]
]
n = NeuralNetwork()
stats = n.train(ground_truth_dataset, 100001, 0.001)
epochs = stats[0]
min_losses = stats[1]
avg_losses = stats[2]
max_losses = stats[3]
with open("model.bin", "wb") as f:
pickle.dump(n, f)
plt.ylabel("Loss")
plt.xlabel("Epoch")
plt.plot(epochs, min_losses, label="Min loss")
plt.plot(epochs, avg_losses, label="Avg loss")
plt.plot(epochs, max_losses, label="Max loss")
plt.legend(loc="center")
plt.show()