\section{Astro particles}
\subsection{Introduction}
We applied several classifing algorithms on the Astros dataset\footnote{http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html\#svmguide1}. We tested the following algorithms:
\begin{itemize}
  \item[\textbullet] Random Classifier
  \item[\textbullet] Majority Classifier
  \item[\textbullet] 3NN
  \item[\textbullet] 5NN
\end{itemize}

We tried different combinaison of pretreatment:
\begin{itemize}
  \item[\textbullet] None
  \item[\textbullet] Cleaning
  \item[\textbullet] Distilling
  \item[\textbullet] Cleaning, distilling and cleaning
\end{itemize}
\subsection{Results}
\begin{figure}[h!]
	\begin{center}
		\includegraphics[width=12cm]{images/astros/astros}
	\end{center}
	\caption{Benchmark results on ASTROS dataset}
\end{figure}

\begin{figure}[!h]
	\begin{center}
		\includegraphics[width=12cm]{images/astros/astros-cleaned}
	\end{center}
	\caption{Benchmark results on cleaned ASTROS dataset}
\end{figure}

\begin{figure}[!h]
	\begin{center}
		\includegraphics[width=12cm]{images/astros/astros-distilled}
	\end{center}
	\caption{Benchmark results on distilled ASTROS dataset}
\end{figure}

\begin{figure}[!h]
	\begin{center}
		\includegraphics[width=12cm]{images/astros/astros-cleaned-distilled-cleaned}
	\end{center}
	\caption{Benchmark results on cleaned, distilled and cleaned ASTROS dataset}
\end{figure}
\newpage
\subsection{Comments}
On the astros dataset, the KNN algorithm is the more efficient with a preliminary clean of the wrong labels. The distilled dataset, or cleaned distilled and cleaned dataset has bad results.