V. Consonni, D. Ballabio, and R. Todeschini, Parameter for QSAR Validation, Journal of Chemical Information and Modeling, vol.49, issue.7, pp.1669-1678, 2009.
DOI : 10.1021/ci900115y

. Datatop, TNO Defence, Security and Safety, Energetic Materials Research Group, 2005.

W. M. Haynes, CRC Handbook of Chemistry and Physics, 2011.

P. Gramatica, Principles of QSAR models validation: internal and external, QSAR & Combinatorial Science, vol.15, issue.5, pp.694-701, 2007.
DOI : 10.1002/qsar.200610151

J. Jaworska, N. Nikolova-jeliazkova, and T. Aldenberg, QSAR applicability domain estimation by projection of the training set descriptor space: a review, Altern. Lab. Anim, vol.33, pp.445-459, 2005.

M. Karelson, Molecular Descriptors in QSAR, 2000.

A. R. Katritzky, R. Petrukhin, R. Jain, and M. Karelson, QSPR Analysis of Flash Points, Journal of Chemical Information and Computer Sciences, vol.41, issue.6, pp.1521-1530, 2001.
DOI : 10.1021/ci010043e

J. Koziol, Neural network modelling of physical properties of chemical compounds, Int. J. Quantum Chem, vol.84, pp.17-26, 2001.

L. I. Lin, A Concordance Correlation Coefficient to Evaluate Reproducibility, Biometrics, vol.45, issue.1, pp.255-268, 1989.
DOI : 10.2307/2532051

L. I. Lin, Assay Validation Using the Concordance Correlation Coefficient, Biometrics, vol.48, issue.2, pp.599-604, 1992.
DOI : 10.2307/2532314

F. Lindgren, B. Hansen, and W. Karcher, Model validation by permutation tests: Applications to variable selection, Journal of Chemometrics, vol.10, issue.5-6, pp.521-532, 1996.
DOI : 10.1002/(SICI)1099-128X(199609)10:5/6<521::AID-CEM448>3.0.CO;2-J

Y. Lu, D. Ng, and M. S. Mannan, Prediction of the Reactivity Hazards for Organic Peroxides Using the QSPR Approach, Industrial & Engineering Chemistry Research, vol.50, issue.3, pp.1515-1522, 2011.
DOI : 10.1021/ie100833m

T. I. Netzeva, A. Worth, T. Aldenberg, R. Benigni, M. T. Cronin et al., Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop 52, Altern. Lab. Anim, vol.33, pp.155-173, 2005.

G. P. Romanelli, L. R. Cafferata, and E. A. Castro, Ameliorate QSPR study of alkyl Hydroperoxides, Russian Journal of General Chemistry, vol.71, issue.2, pp.257-260, 2001.
DOI : 10.1023/A:1012307623527

C. Rücker, G. Rücker, and M. Meringer, y-Randomization and Its Variants in QSPR/QSAR, Journal of Chemical Information and Modeling, vol.47, issue.6, pp.2345-2357, 2007.
DOI : 10.1021/ci700157b

G. Schüürmann, R. Ebert, J. Chen, B. Wang, and R. Kühne, External Validation and Prediction Employing the Predictive Squared Correlation Coefficient ??? Test Set Activity Mean vs Training Set Activity Mean, Journal of Chemical Information and Modeling, vol.48, issue.11, pp.2140-2145, 2008.
DOI : 10.1021/ci800253u

U. , S. Sg, and . Ac, Recommendations on the transport of dangerous goods: Manual of tests and criteria, United Nations, vol.105, 2011.

A. Tropsha, P. Gramatica, and V. K. Gombar, The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models, QSAR & Combinatorial Science, vol.38, issue.1, pp.69-77, 2003.
DOI : 10.1002/qsar.200390007