A Proposal of a Methodological Framework with Experimental Guidelines to Investigate Clustering Stability on Financial Time Series. Marti, G.; Very, P.; Donnat, P.; and Nielsen, F. In Li, T.; Kurgan, L. A.; Palade, V.; Goebel, R.; Holzinger, A.; Verspoor, K.; and Wani, M. A., editors, 14th IEEE International Conference on Machine Learning and Applications, ICMLA 2015, Miami, FL, USA, December 9-11, 2015, pages 32–37, 2015. IEEE.
A Proposal of a Methodological Framework with Experimental Guidelines to Investigate Clustering Stability on Financial Time Series [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/icmla/MartiVDN15,
  author    = {Gautier Marti and
               Philippe Very and
               Philippe Donnat and
               Frank Nielsen},
  editor    = {Tao Li and
               Lukasz A. Kurgan and
               Vasile Palade and
               Randy Goebel and
               Andreas Holzinger and
               Karin Verspoor and
               M. Arif Wani},
  title     = {A Proposal of a Methodological Framework with Experimental Guidelines
               to Investigate Clustering Stability on Financial Time Series},
  booktitle = {14th {IEEE} International Conference on Machine Learning and Applications,
               {ICMLA} 2015, Miami, FL, USA, December 9-11, 2015},
  pages     = {32--37},
  publisher = {{IEEE}},
  year      = {2015},
  url       = {https://doi.org/10.1109/ICMLA.2015.11},
  doi       = {10.1109/ICMLA.2015.11},
  timestamp = {Wed, 16 Oct 2019 14:14:53 +0200},
  biburl    = {https://dblp.org/rec/conf/icmla/MartiVDN15.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
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