Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks
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Irene Córdoba-Sánchez | Eduardo C. Garrido-Merchán | Daniel Hernández-Lobato | Concha Bielza | Pedro Larrañaga | C. Bielza | D. Hernández-Lobato | P. Larrañaga | Irene Córdoba-Sánchez | E.C. Garrido-Merchán
[1] Radford M. Neal. Pattern Recognition and Machine Learning , 2007, Technometrics.
[2] Pedro M. Domingos. A few useful things to know about machine learning , 2012, Commun. ACM.
[3] Olga Vitek,et al. From Correlation to Causality: Statistical Approaches to Learning Regulatory Relationships in Large-Scale Biomolecular Investigations. , 2016, Journal of proteome research.
[4] Tao Li,et al. Differentially private classification with decision tree ensemble , 2018, Appl. Soft Comput..
[5] Brandon M. Malone,et al. Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction , 2017, Machine Learning.
[6] Rong-Her Chiu,et al. PREDICTING CUSTOMER RETENTION LIKELIHOOD IN THE CONTAINER SHIPPING INDUSTRY THROUGH THE DECISION TREE APPROACH , 2017 .
[7] J. Gausemeier,et al. Industrie 4 . 0 in a Global Context Strategies for Cooperating with International Partners , 2016 .
[8] Luis Pérez-Lombard,et al. A review on buildings energy consumption information , 2008 .
[9] Tom Burr,et al. Causation, Prediction, and Search , 2003, Technometrics.
[10] Li Da Xu,et al. Industry 4.0: state of the art and future trends , 2018, Int. J. Prod. Res..
[11] Javier Prieto,et al. Semantic Analysis System for Industry 4.0 , 2018, KMO.
[12] Bart De Schutter,et al. Combining knowledge and historical data for system-level fault diagnosis of HVAC systems , 2017, Eng. Appl. Artif. Intell..
[13] Matthew W. Hoffman,et al. Predictive Entropy Search for Efficient Global Optimization of Black-box Functions , 2014, NIPS.
[14] Eduardo C. Garrido-Merchán,et al. Dealing with Categorical and Integer-valued Variables in Bayesian Optimization with Gaussian Processes , 2017, Neurocomputing.
[15] Carl E. Rasmussen,et al. Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.
[16] Marco Scutari,et al. Learning Bayesian Networks with the bnlearn R Package , 2009, 0908.3817.
[17] Don-Lin Yang,et al. Automatic machine status prediction in the era of Industry 4.0: Case study of machines in a spring factory , 2017, J. Syst. Archit..
[18] Brandon M. Malone,et al. Impact of Learning Strategies on the Quality of Bayesian Networks: An Empirical Evaluation , 2015, UAI.
[19] Andrew P. Bradley,et al. The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..
[20] George K. Karagiannidis,et al. Efficient Machine Learning for Big Data: A Review , 2015, Big Data Res..
[21] David W. Hosmer,et al. Applied Logistic Regression , 1991 .
[22] Nando de Freitas,et al. Taking the Human Out of the Loop: A Review of Bayesian Optimization , 2016, Proceedings of the IEEE.
[23] Marcelo Ângelo Cirillo,et al. Data classification with binary response through the Boosting algorithm and logistic regression , 2017, Expert Syst. Appl..
[24] Tom Minka,et al. Expectation Propagation for approximate Bayesian inference , 2001, UAI.
[25] Jasper Snoek,et al. Practical Bayesian Optimization of Machine Learning Algorithms , 2012, NIPS.
[26] Won Y. Lee,et al. Classification Techniques for Fault Detection and Diagnosis of an Air-Handling Unit | NIST , 1999 .
[27] Korbinian Strimmer,et al. Entropy Inference and the James-Stein Estimator, with Application to Nonlinear Gene Association Networks , 2008, J. Mach. Learn. Res..
[28] Peter Bühlmann,et al. Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm , 2007, J. Mach. Learn. Res..
[29] Yi Wang,et al. Intelligent predictive maintenance for fault diagnosis and prognosis in machine centers: Industry 4.0 scenario , 2017 .
[30] Diego Colombo,et al. Order-independent constraint-based causal structure learning , 2012, J. Mach. Learn. Res..
[31] Yvan Beauregard,et al. A predictive preference model for maintenance of a heating ventilating and air conditioning system , 2015 .
[32] Concha Bielza,et al. Bayesian networks in neuroscience: a survey , 2014, Front. Comput. Neurosci..
[33] Boris Otto,et al. Design Principles for Industrie 4.0 Scenarios , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).
[34] Steffen L. Lauritzen,et al. Independence properties of directed markov fields , 1990, Networks.
[35] Constantin F. Aliferis,et al. The max-min hill-climbing Bayesian network structure learning algorithm , 2006, Machine Learning.