def main():
"""This is the driver program for showing results from part 1.
Uncomment the code below if you need to pickle a new trained
perceptron."""
digitsMatrices, digitsTargets = loadPatterns("digits_train.txt")
digitsTests, digitsTestTargets = loadPatterns("digits_test.txt")
target = np.array(())
for p in range(2500):
arrayOfTen = np.array(())
beginning = np.append(np.zeros(digitsTargets[p]), np.ones(1))
arrayOfTen = np.append(beginning, np.zeros(9 - digitsTargets[p]))
target = np.append(target, arrayOfTen)
target = np.reshape(target, (2500, 10))
"""trainEta = 1 #Change only these when tweaking for better results
numberOfPatterns = 10000 #Change only these when tweaking for better results
print("Initialized Perceptron: \n")
digitsPerceptron = Perceptron(196,10,3,.1)
digitsPerceptron.train(digitsMatrices,target,numberOfPatterns,trainEta)
digitsPerceptron.save("part3.dat")"""
newPerceptron = Perceptron(196, 10, 3, .1)
unPickled = newPerceptron.load("part3.dat")
confusion = np.zeros((10, 10), "int")
for k in range(2500):
row = k // 250
col = np.argmax(unPickled.test(digitsTests[k]))
confusion[row, col] += 1
print(confusion)
"""threshold = .23 #Change only these when tweaking for better results
def main():
"""This is the driver program for showing results from part 1.
Uncomment the code below if you need to pickle a new trained
perceptron."""
twoMatrices, twoTargets = loadPatterns("digits_train.txt")
twoTests, twoTestsTargets = loadPatterns("digits_test.txt")
target = np.zeros(2500)
target[500:750] = 1
falsePositives = 0
misses = 0
"""
trainEta = 1 #Change only these when tweaking for better results
numberOfPatterns = 2000 #Chang only these when tweaking for better results
print("Initialized Perceptron: \n")
twoPerceptron = Perceptron(196,1,3,.1)
twoPerceptron.train(twoMatrices,target,numberOfPatterns,trainEta)
twoPerceptron.save()"""
newPerceptron = Perceptron(196, 1, 3, .1)
unPickled = newPerceptron.load('weights.dat')
threshold = .23 #Change only these when tweaking for better results
#print("Expect greater than " + str(threshold) +": " + str(unPickled.test(twoTests[521])))
for i in range(len(twoTests)):
test = unPickled.test(twoTests[i])
if test >= threshold and target[i] == 0:
falsePositives += 1
if test < threshold and target[i] == 1:
misses += 1
print("Misses: " + str(misses) + "/250")
print("False Positives: " + str(falsePositives) + "/2250")
def main():
"""This is the driver program for showing results from part 1."""
inputArray = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
targetXOR = np.array([[0], [1], [1], [0]])
print("Initializing 1X3 Perceptron....")
testP = Perceptron(2, 1, 3)
print(str(testP) + "\n")
print("\n" + "Testing learning XOR: \n")
testP.train(inputArray, targetXOR)
print("Training results:\n")
print("Expect Close to 0: " + str(testP.test(np.array([0, 0]))))
print("Expect Close to 1: " + str(testP.test(np.array([0, 1]))))
print("Expect Close to 1: " + str(testP.test(np.array([1, 0]))))
print("Expect Close to 0: " + str(testP.test(np.array([1, 1]))) + "\n")
