def variance(xs: List[float]) -> float:
"""Almost the average squares deviation from the mean"""
assert len(xs) >= 2, "variance requires at least two elements"
n = len(xs)
deviations = de_mean(xs)
return sum_of_squares(deviations) / (n - 1)
def variance(x):
"""assumes x has at least two elements
:x: list
:returns: variance integer
"""
n = len(x)
deviations = de_mean(x)
return sum_of_squares(deviations) / (n - 1)
def variance(x):
"""assumes x has at least two elements"""
n = len(x)
mean_deviations = de_mean(x)
return sum_of_squares(mean_deviations) / n - 1
def variance(x):
n = len(x)
deviations = de_mean(x)
return sum_of_squares(deviations) / (n - 1)
def variance(x, len_x):
deviations = de_mean(x,len_x)
return sum_of_squares(deviations) / len_x
def variance(xs: List[float]) -> float:
return sum_of_squares(de_mean(xs)) / (len(xs) - 1)
def variance(xs: List[float]) -> float:
assert len(xs) >= 2, "at least 2 values"
n = len(xs)
deviations = de_mean(xs)
return sum_of_squares(deviations) / (n - 1)
def variance(xs: List[float]) -> float:
"Average squared difference from the mean (however we divide by n-1 instead of n)"
n = len(xs)
deviations = de_mean(xs)
return sum_of_squares(deviations) / (n - 1)
def variance(x):
"""assumes x has at least two elements"""
n = len(x)
deviations = de_mean(x)
return sum_of_squares(deviations) / (n - 1)
def variance(x):
'''assumes x has at least two elements'''
n = len(x)
deviations = de_mean(x)
return sum_of_squares(deviations) / (n - 1)
def variance(x):
n = len(x)
deviatations = de_mean(x)
return sum_of_squares(deviatations) / (n - 1)
def test_sum_of_squares(self):
self.assertEqual(6, sum_of_squares([1, 2, 1]))
def variance(x):
#xには値を少なくとも2つあることを前提とする
n = len(x)
deviations = de_mean(x)
return sum_of_squares(deviations) / (n - 1)
def variance(x):
"""assumes x has at least two elements"""
n = len(x)
deviations = de_mean(x)
return la.sum_of_squares(deviations) / (n - 1)
C = la.vector_subtract(A, B)
print("A - B = ", C)
C = la.vector_sum([A, B])
print("A and B summary = ", C)
C = la.scalar_multiply(10, A)
print("10 * A = ", C)
C = la.vector_mean([A, B])
print("A and B mean = ", C)
C = la.dot(A, B)
print("A dot B = ", C)
C = la.sum_of_squares(A)
print("A^2's summary = ", C)
C = la.magnitude(A)
print("A's magnitude = ", C)
C = la.distance(A, B)
print("A's distance = ", C)
print()
print("*** matrix ......")
M = [[1, 2, 3], [5, 6, 7], [3, 6, 9]]
print("M = ", M)
shape = la.shape(M)
print("M's shape = ", shape)
def variance(x):
# type: (object) -> object
"""assumes x has at least two elements"""
n = len(x)
deviations = de_mean(x)
return sum_of_squares(deviations) / (n - 1)
def magnitude(v):
return math.sqrt(sum_of_squares(v))
def variance(x):
n = len(x) #204
deviations = de_mean(x) #16553,33
return sum_of_squares(deviations) / (n-1)
def squared_distance(v, w):
return sum_of_squares(vector_subtract(v, w))
