T. Chen and C. Guestrin, XGBoost, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '16, 2016.
DOI : 10.1109/SSDBM.2007.27

T. Ribeiro, M. Singh, S. Guestrin, and C. , "Why Should I Trust You?", Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '16, 2016.
DOI : 10.1109/CVPR.2015.7298594

Z. C. Lipton, The Mythos of Model Interpretability, ICML Workshop on Human Interpretability in Machine Learning, 2016.

S. Hara and K. Hayashi, Making Tree Ensembles Interpretable, ICML Workshop on Human Interpretability in Machine Learning, 2016.

E. Sobhani-tehrani and K. Khorasani, Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach, 2009.
DOI : 10.1007/978-0-387-92907-1

C. Gallego-ortiz and A. L. Martel, Interpreting extracted rules from ensemble of trees: Application to computer-aided diagnosis of breast MRI, ICML Workshop on Human Interpretability in Machine Learning, 2016.

B. Letham, C. Rudin, T. H. Mccormick, and D. Madigan, Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model, The Annals of Applied Statistics, vol.9, issue.3, pp.1350-1371, 2015.
DOI : 10.1214/15-AOAS848SUPPB

S. Hochreiter and J. Schmidhuber, Long Short-Term Memory, Neural Computation, vol.4, issue.8, pp.1735-1780, 1997.
DOI : 10.1016/0893-6080(88)90007-X