def main():
digits = sklearn.datasets.load_digits()
data = sklearn.preprocessing.scale(digits.data)
print(elice_utils.display_digits(digits, 113))
benchmark(data, digits.target, 1, 64)
def main():
digits = sklearn.datasets.load_digits()
data = sklearn.preprocessing.scale(digits.data)
print(elice_utils.display_digits(digits, 113))
benchmark(data, digits.target, 1, 64)
def main():
# 1
digits = sklearn.datasets.load_digits()
data = sklearn.preprocessing.scale(digits.data)
# 2
# Try looking at different digits by changing index from 0 to 1796.
print(elice_utils.display_digits(digits, 113))
# 4
benchmark(data, digits.target, 1, 64)
def main():
# 1
digits = sklearn.datasets.load_digits()
data = sklearn.preprocessing.scale(digits.data)
# 2
# Try looking at different digits by changing index from 0 to 1796.
print(elice_utils.display_digits(digits, 113))
# 4
benchmark(data, digits.target, 1, 64)
def visualize(clf, X, Y, images, right, wrong):
counter = 0
for x, y in zip(X, Y):
predicted = clf.predict([x])[0]
if predicted == y:
right -= 1
if right < 0:
continue
elice_utils.display_digits(
images[1600 + counter],
"Right: Real value: %d (expected %d)" % (y, predicted))
else:
wrong -= 1
if wrong < 0:
continue
elice_utils.display_digits(
images[1600 + counter],
"Wrong: Real value: %d (expected %d)" % (y, predicted))
counter += 1
