02machine_learning_Linear regression model

Linear regression model

regression model predicts numbers

supervised learning model data has "right answers"

Classification model predicts catogories

 

example

terminology

x : "input" variable feature

y : "output" variable

"target" variable

m :number of training examples

(x,y) : single training example

(xi,yi) = ith training example(1st,2st,3st,...)

for example

 

 

 

xmind

training set:features and targets
->
learning algorithm
->
f

 

 

$$
x->f->\widehat{y}\\ x:feature \quad f:model \quad \widehat{y}:prediction(estimated \ y)
$$

 

represent f

$$
f_w,_b(x) = wx+b
$$

linear regression with one variable.

example: