deletions | additions       diff --git a/section_Conclusion_begin_itemize_item__.tex b/section_Conclusion_begin_itemize_item__.tex  index 75122f1..c642a04 100644  --- a/section_Conclusion_begin_itemize_item__.tex  +++ b/section_Conclusion_begin_itemize_item__.tex 
...
\item find a way to measure how well are our cluster  \end{itemize}  The statements about the results remain too subjective, it subjective though. It  lacks an objective measure of the quality of the clusters. I tried to use silhouette index, which is a common way to measure the quality of a clusters' set \cite{parisot:tel-00978520}. The silhouette index belong to $[-1,1]$: it is near to $1$ if the cluster are perfectly separated to each other and near to $-1$ in the opposite case. However I always get values near to $0$ when I compute it to my results, which does not give much information since it is a very general index, and thus there is no telling whether it suits to our problem or not. A further step would consist in developing such an index designed for this problem and to compare the results with other cluster sets generated with state-of-the-art metrics (as LCSS or DTW for example).