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Machine Learning -Basic
Cost function
Model:
f
w
,
b
(
x
(
i
)
)
=
w
x
(
i
)
+
b
f_{w,b}(x^{(i)}) = wx^{(i)} + b
f
w
,
b
(
x
(
i
)
)
=
w
x
(
i
)
+
b
parameters :
w,b - (模型的参数)/coefficients(系数)/weights(权重)
cost function:
J
(
w
,
b
)
=
1
2
m
∑
i
=
0
m
−
1
(
f
w
,
b
(
x
(
i
)
)
−
y
(
i
)
)
2
J(w,b) = \frac{1}{2m} \sum\limits_{i = 0}^{m-1} (f_{w,b}(x^{(i)}) - y^{(i)})^2
J
(
w
,
b
)
=
2
m
1
i
=
0
∑
m
−
1
(
f
w
,
b
(
x
(
i
)
)
−
y
(
i
)
)
2
Objective:
minimize
w
,
b
J
(
w
)
\underset{w,b}{\text{minimize}} J(w)
w
,
b
minimize
J
(
w
)
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Last updated
1 year ago
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