calculate the sum of squared residuals more pythonic
This commit is contained in:
parent
e2f569ff97
commit
90b5fb26ec
1 changed files with 1 additions and 3 deletions
|
@ -16,9 +16,7 @@ yn = [6, 5, 7, 10, 11, 12, 14]
|
||||||
#
|
#
|
||||||
# For each data point the vertical error/residual is x*b1 + b2 - y. We want to
|
# For each data point the vertical error/residual is x*b1 + b2 - y. We want to
|
||||||
# minimize the sum of the squared residuals (least squares).
|
# minimize the sum of the squared residuals (least squares).
|
||||||
S = Symbol('0')
|
S = sum((xn[i] * b1 + b2 - yn[i]) ** 2 for i in range(0, len(xn)))
|
||||||
for i in range(0, len(xn)):
|
|
||||||
S += (xn[i] * b1 + b2 - yn[i]) ** 2
|
|
||||||
print(S)
|
print(S)
|
||||||
|
|
||||||
# Minimize S by setting its partial derivatives to zero.
|
# Minimize S by setting its partial derivatives to zero.
|
||||||
|
|
Loading…
Add table
Add a link
Reference in a new issue