内容来自于机器学习课程
Gradient Descent 梯度下降
So we have our hypothesis function and we have a way of measuring how well it fits into the data. Now we need to estimate the parameters in the hypothesis function. That’s where gradient descent comes in.
use Gradient Descent to minimize some function
:= assignment
= truth assert
learning rate α , how big a step we take when updating my parameter
simultaneous update 同时更新
Gradient Descent Intuition
derivate term
learning rate
gradient descent can converge to a local minimum, even with the learning rate α fixed.
Gradient Descent For Linear
convex function
导数部分推导过程
The point of all this is that if we start with a guess for our hypothesis and then repeatedly apply these gradient descent equations, out hypothesis will become more and more accurate.
batch gradient descent