}
}
# initialize the neural network with full data set
mpl = Perceptron(y, x, Options)
print('Params: ' + str(len(mpl.params)))
print(mpl.size)
print('')
print('Cost Function: ' + str(mpl.cost_function(mpl.params)))
print('Accuracy : ' + str(mpl.accuracy(mpl.h, yl, 1)))
print('')
print('* Gradient Descent')
mpl.gradient_descent(10)
print('Accuracy : ' + str(mpl.accuracy(mpl.h, yl, 1)))
print('')
print('* LBFGS Optimization')
mpl.lbfgs(150)
print('Cost Function: ' + str(mpl.cost_function(mpl.params)))
print('Accuracy : ' + str(mpl.accuracy(mpl.h, yl, 1)))
print('')
print('Mean: ' + str(np.mean(mpl.params)))
print('Sum : ' + str(np.sum(mpl.params)))
print('Norm: ' + str(np.linalg.norm(mpl.params)))
# print(pd.DataFrame(mpl.params))
