XGBoost, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '16, 2016. ,
DOI : 10.1109/SSDBM.2007.27
"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
The Mythos of Model Interpretability, ICML Workshop on Human Interpretability in Machine Learning, 2016. ,
Making Tree Ensembles Interpretable, ICML Workshop on Human Interpretability in Machine Learning, 2016. ,
Fault Diagnosis of Nonlinear Systems Using a Hybrid Approach, 2009. ,
DOI : 10.1007/978-0-387-92907-1
Interpreting extracted rules from ensemble of trees: Application to computer-aided diagnosis of breast MRI, ICML Workshop on Human Interpretability in Machine Learning, 2016. ,
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
Long Short-Term Memory, Neural Computation, vol.4, issue.8, pp.1735-1780, 1997. ,
DOI : 10.1016/0893-6080(88)90007-X