A. Bagnall and J. Lines, «An experimental evaluation of nearest neighbour time series classification, 2014.

A. Bagnall, J. Lines, J. Hills, and A. Bostrom, «Time-series classification with cote : The collective of transformation-based ensembles, IEEE Transactions on Knowledge and Data Engineering, vol.27, issue.9, p.57, 2015.

M. G. Baydogan and G. R. , «Learning a symbolic representation for multivariate time series classification, Data Mining and Knowledge Discovery, vol.29, issue.2, p.52, 2015.

J. Bergstra and Y. Bengio, «Random search for hyper-parameter optimization, Journal of Machine Learning Research, vol.13, p.53, 2012.

A. Bondu, D. Gay, V. Lemaire, M. Boullé, and E. Cervenka, «Fears : a feature and representation selection approach for time series classification, p.48, 2019.

L. Breiman, Machine learning, vol.45, issue.1, pp.5-32, 2001.

M. G. Baydogan and G. R. , «Learning a symbolic representation for multivariate time series classification, Data Mining and Knowledge Discovery, vol.29, issue.2, p.93, 2015.

J. Dem?ar, «Statistical comparisons of classifiers over multiple data sets, Machine learning research, vol.7, pp.1-30, 2006.

A. Plaud, E. Nguifo, and J. Charreyron, «Classification des séries temporelles multivariées par l'usage de mgrams, p.96, 2019.

P. Schäfer and U. Leser, «Multivariate time series classification with WEA-SEL+MUSE, vol.76, p.93, 2017.

. .. Travail-effectué, 3.3 Théorie de l'apprentissage multi-vues, Conclusion Sommaire 6.1, vol.118

.. .. Références,

A. Goyal, E. Morvant, P. Germain, and M. Amini, «Multiview boosting by controlling the diversity and the accuracy of view-specific voters, Neurocomputing, vol.358, pp.81-92, 2019.

Y. Lecun, Y. Bengio, and G. Hinton, Deep learning», nature, vol.521, p.121, 2015.

P. Naïm, P. Wuillemin, P. Leray, O. Pourret, and A. Becker, Réseaux bayésiens, vol.3, p.120, 1999.

, Calibration des séries temporelles multivariées issues d'accéléromètres

, Engelbert Mephu Nguifo, vol.1

O. A. Basir, S. H. Jamali, W. B. Miners, and J. Toonstra, Method of correcting the orientation of a freely installed accelerometer in a vehicle, 2013.

J. M. Berthelot, Mécanique des solides rigides, 1999.

R. Bhoraskar, N. Vankadhara, B. Raman, and P. Kulkarni, Wolverine : Traffic and road condition estimation using smartphone sensors, 2012 Fourth International Conference on Communication Systems and Networks (COMSNETS 2012), pp.1-6, 2012.

M. R. Carlos, L. C. González, F. Martínez, and R. Cornejo, Evaluating reorientation strategies for accelerometer data from smartphones for its applications, Ubiquitous Computing and Ambient Intelligence, pp.407-418, 2016.

L. Euler, Du mouvement de rotation des corps solides autour d'un axe variable, 1765.

K. Hemanth, V. Talasila, and S. Rao, Calibration of 3-axis magnetometers, IFAC Proceedings Volumes, vol.45, pp.175-178, 2012.

I. Jolliffe and J. Cadima, Principal component analysis : a review and recent developments, Philosophical Transactions of the Royal Society of London Series A, vol.374, p.20150202, 2016.

E. Kostelich and T. Schreiber, Noise reduction in chaotic time-series data : A survey of common methods, Nonlinear, and Soft Matter Physics, vol.48, issue.3, pp.1752-1763, 1993.

J. Large, P. Southam, and A. J. Bagnall, Can automated smoothing significantly improve benchmark time series classification algorithms ?, 2018.

K. Li, M. Lu, F. Lu, Q. Lv, L. Shang et al., Personalized driving behavior monitoring and analysis for emerging hybrid vehicles, Pervasive Computing, pp.1-19, 2012.