deletions | additions       diff --git a/section_Conclusion_begin_itemize_item__.tex b/section_Conclusion_begin_itemize_item__.tex  index c642a04..f605e12 100644  --- a/section_Conclusion_begin_itemize_item__.tex  +++ b/section_Conclusion_begin_itemize_item__.tex 
...
\end{itemize}  The statements about the results remain too 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 belongs  to $[-1,1]$: it is near close  to $1$ if the cluster are perfectly separated to each other and near close  to $-1$ in the opposite case. However I always get values near rather close  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 Therefore,  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).