Linear regrssion, cost func. , Logistic
linear regression, cost, logistic Linear Regression 정리Hypothesis H(x)=W∗x+bH(x)=W*x+b H(x)=W∗x+b H(x1,x2,x3)=w1x1+w2x+w3x3+bH(x1,x2,x3)=w_{1}x_{1}+w_{2}x+w_{3}x_{3}+bH(x1,x2,x3)=w1x1+w2x+w3x3+b 실제 구현시 H(x)=XH (매트릭스를 사용한다) bias는 간략히 하기위해 생략 Cost Function cost(W,b)=1m∑i=1m(H(x)i−yi)2)cost(W,b) = \frac{1}{m}\sum_{i=1}^{m}(H(x)^i-y^i)^2)cost(W,b)=m1i=1∑m(H(x)i−yi)2) cost(W,b)=1m∑i=1m(H(x1,x2,..
2018. 1. 26.