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[regression] some more notes

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Jan Benda
2019-12-12 08:49:27 +01:00
parent a7e64a5c6d
commit f2778e2fe2
3 changed files with 15 additions and 7 deletions
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14
regression/lecture/regression-chapter.tex
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@@ -23,15 +23,21 @@
\subsection{Start with one-dimensional problem!}
\begin{itemize}
\item Just the root mean square as a function of the slope
\item 1-d gradient
\item Let's fit a cubic function $y=cx^3$ (weight versus length of a tiger)
\item Introduce the problem, $c$ is density and form factor
\item How to generate an artificial data set (refer to simulation chapter)
\item How to plot a function (do not use the data x values!)
\item Just the mean square error as a function of the factor c
\item Also mention the cost function for a straight line
\item 1-d gradient, NO quiver plot (it is a nightmare to get this right)
\item 1-d gradient descend
\item Homework is to do the 2d problem!
\item Describe in words the n-d problem.
\item Homework is to do the 2d problem with the straight line!
\end{itemize}
\subsection{Linear fits}
\begin{itemize}
\item Polyfit is easy: unique solution!
\item Polyfit is easy: unique solution! $c x^2$ is also a linear fit.
\item Example for overfitting with polyfit of a high order (=number of data points)
\end{itemize}