How to solve multivariate linear regression?

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Suppose $x in R^2$, $Ain R^2X2$ and $ bin R^2$.

$haty=Ax+b$ where $haty$ is predicted output.

We have to find $A$ and $b$ in terms of $X$ and $Y$ such that squared L2 distance between $hatY$ and $Y$ is minimised. Where $X=[x_1$ $x_2$ $...$ $x_n]$, $Y=[y_1$ $y_2$ $...$ $y_n]$ and $hatY=[haty_1$ $haty_2$ $...$ $haty_n]$






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    Suppose $x in R^2$, $Ain R^2X2$ and $ bin R^2$.

    $haty=Ax+b$ where $haty$ is predicted output.

    We have to find $A$ and $b$ in terms of $X$ and $Y$ such that squared L2 distance between $hatY$ and $Y$ is minimised. Where $X=[x_1$ $x_2$ $...$ $x_n]$, $Y=[y_1$ $y_2$ $...$ $y_n]$ and $hatY=[haty_1$ $haty_2$ $...$ $haty_n]$






    linear-regression







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      up vote
      0
      down vote

      favorite









      up vote
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      down vote

      favorite











      Suppose $x in R^2$, $Ain R^2X2$ and $ bin R^2$.

      $haty=Ax+b$ where $haty$ is predicted output.

      We have to find $A$ and $b$ in terms of $X$ and $Y$ such that squared L2 distance between $hatY$ and $Y$ is minimised. Where $X=[x_1$ $x_2$ $...$ $x_n]$, $Y=[y_1$ $y_2$ $...$ $y_n]$ and $hatY=[haty_1$ $haty_2$ $...$ $haty_n]$






      linear-regression







      share|cite|improve this question













      Suppose $x in R^2$, $Ain R^2X2$ and $ bin R^2$.

      $haty=Ax+b$ where $haty$ is predicted output.

      We have to find $A$ and $b$ in terms of $X$ and $Y$ such that squared L2 distance between $hatY$ and $Y$ is minimised. Where $X=[x_1$ $x_2$ $...$ $x_n]$, $Y=[y_1$ $y_2$ $...$ $y_n]$ and $hatY=[haty_1$ $haty_2$ $...$ $haty_n]$






      linear-regression




      linear-regression






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      asked Sep 5 at 8:27









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