1. Modeling seasonality
w1 models the linear trend of the overall process.
w2 models the seasonal component sinusoid with a period of 12
and you do not know when the trend occurs so there exists a phase shift.
2. Regression model
Now we are looking at the coeffiencts,for instanc,e the number of bedrroms, And
what‘s the predicted change in the value of my house with everything else fixed.
Note:
the interpretation is in the context of what you have in the model. If the
square footage is fixed, the increse of the number of bedroom does not always
increase the value of the house.
3. RSS in matrix form and the gradient
and the gradient of RSS is equal to：
4.The close-form solution
we can set the gradient to be zero to find the minimum:
and we can get the W that we want.
5. Gradien descent
机器学习笔记（Washington University）- Regression Specialization-week two
原文：http://www.cnblogs.com/climberclimb/p/6798811.html