answer = 0
if (sampleDot.y > line.f(sampleDot.x)):
answer = 1
else:
answer = -1
perceptron.Train(answer)
# Estimating each dots from the set
goodGuessCount = 0
for dot in dataset.dots:
perceptron.SetInputs([dot.x, dot.y, bias])
if (dot.y > line.f(dot.x)):
answer = 1
else:
answer = -1
guess = perceptron.Estimate()
if (guess == answer):
goodGuessCount += 1
color = ''
if (guess == 1):
color = 'ro'
else:
color = 'bo'
plt.plot(dot.x, dot.y, color)
perceptron.accuracy = goodGuessCount / len(dataset.dots)
print("Loss = " + "{:.2f}".format(1 - perceptron.GetAccuracy()))
# Drawing an estimated separation line from the model weights
w0 = perceptron.weights[0]
w1 = perceptron.weights[1]
