Linear regrssion, cost func. , Logistic

Linear Regression 정리

Hypothesis

$H(x)=W*x+b$
$H(x1,x2,x3)=w_{1}x_{1}+w_{2}x+w_{3}x_{3}+b$

실제 구현시 H(x)=XH
(매트릭스를 사용한다)
bias는 간략히 하기위해 생략

Cost Function

$cost(W,b) = \frac{1}{m}\sum_{i=1}^{m}(H(x)^i-y^i)^2)$
$cost(W,b) = \frac{1}{m}\sum_{i=1}^{m}(H(x_{1},x_{2},x_{3})^i-y^i)^2$

Logistic hypothesis

$H(x)=\frac{1}{1+e^(-W^T X)}$