✏️
LiHang-TongJiXueXiFangFa
More
Search
Ctrl + K
多分类逻辑回归模型
假设Y的取值集合是${1, 2, \cdots, K}$，则
P
(
Y
=
k
∣
x
)
=
exp
(
w
k
⋅
x
)
1
+
∑
k
=
1
K
−
1
e
x
p
(
w
k
⋅
x
)
P
(
Y
=
K
)
=
1
1
+
∑
k
=
1
K
−
1
e
x
p
(
w
k
⋅
x
)
\begin{aligned} P(Y=k|x) = \frac{\exp (w_k \cdot x)}{1+\sum_{k=1}^{K-1}exp(w_k \cdot x)} \\ P(Y=K) = \frac{1}{1+\sum_{k=1}^{K-1}exp(w_k \cdot x)} \end{aligned}
P
(
Y
=
k
∣
x
)
=
1
+
∑
k
=
1
K
−
1
e
x
p
(
w
k
⋅
x
)
exp
(
w
k
⋅
x
)
P
(
Y
=
K
)
=
1
+
∑
k
=
1
K
−
1
e
x
p
(
w
k
⋅
x
)
1
其中$x \in R^{n+1}$，$w_k \in R^{n+1}$
Previous
二分类逻辑回归模型
Next
第6章 最大熵模型
Last updated
4 years ago