Machine Learning: Linear Regression

catetan..

  • Hypothesis function:

h_\theta(x)=\theta_0+\theta_1 x

    • Cost function:

J(\theta_0,\theta_1)=\frac{1}{2m}\sum\limits_{i=1}^m (h_\theta(x^{(i)}) - y^{(i)})^2

  • Gradient descent for linear regression

repeat until convergence \{
\theta_0:=\theta_0-\alpha\frac{1}{m}\sum\limits_{i=1}^m (h_\theta(x^{(i)}) - y^{(i)})
\theta_1:=\theta_1-\alpha\frac{1}{m}\sum\limits_{i=1}^m (h_\theta(x^{(i)}) - y^{(i)}x^{(i)})
\}

 

learningmodel

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