A Bayesian method for the induction of probabilistic networks from data
暂无分享,去创建一个
[1] R. F.,et al. Mathematical Statistics , 1944, Nature.
[2] G. Enderlein. Wilks, S. S.: Mathematical Statistics. J. Wiley and Sons, New York–London 1962; 644 S., 98 s , 1964 .
[3] Philip J. Stone,et al. Experiments in induction , 1966 .
[4] C. N. Liu,et al. Approximating discrete probability distributions with dependence trees , 1968, IEEE Trans. Inf. Theory.
[5] M. Degroot. Optimal Statistical Decisions , 1970 .
[6] David Lindley,et al. Optimal Statistical Decisions , 1971 .
[7] R. W. Robinson. Counting unlabeled acyclic digraphs , 1977 .
[8] Walter Brötz,et al. Electronically produced equidensities from time exposures and instantaneous photographs in the investigation of pool flames , 1980 .
[9] R L Blum,et al. Discovery, confirmation, and incorporation of causal relationships from a large time-oriented clinical data base: the RX project. , 1982, Computers and biomedical research, an international journal.
[10] N. Wermuth,et al. Graphical and recursive models for contingency tables , 1983 .
[11] Peter C. Cheeseman,et al. A Method of Computing Generalized Bayesian Probability Values for Expert Systems , 1983, IJCAI.
[12] Gregory F. Cooper,et al. NESTOR: A Computer-Based Medical Diagnostic Aid That Integrates Causal and Probabilistic Knowledge. , 1984 .
[13] George J. Klir,et al. Reconstructability Analysis: An Overview , 1984 .
[14] T. Speed,et al. Recursive causal models , 1984, Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics.
[15] John R. Anderson,et al. Machine learning - an artificial intelligence approach , 1982, Symbolic computation.
[16] Ross D. Shachter. Intelligent Probabilistic Inference , 1985, UAI.
[17] P. Ut Goff,et al. Machine learning of inductive bias , 1986 .
[18] Judea Pearl,et al. Fusion, Propagation, and Structuring in Belief Networks , 1986, Artif. Intell..
[19] Steen Andreassen,et al. MUNIN - A Causal Probabilistic Network for Interpretation of Electromyographic Findings , 1987, IJCAI.
[20] Max Henrion,et al. An Experimental Comparison of Knowledge Engineering for Expert Systems and for Decision Analysis , 1987, AAAI.
[21] Alice M. Agogino,et al. IDES: influence diagram based expert system , 1987 .
[22] Nasa Ames Reseach. AUTOMATIC PROBABILISTIC KNOWLEDGE ACQUISITION FROM DATA , 1987 .
[23] William B. Gevarter,et al. Automatic probabilistic knowledge acquisition from data , 1987, 1987 IEEE Third International Conference on Data Engineering.
[24] Judea Pearl,et al. The recovery of causal poly-trees from statistical data , 1987, Int. J. Approx. Reason..
[25] David J. Spiegelhalter,et al. Local computations with probabilities on graphical structures and their application to expert systems , 1990 .
[26] Ross D. Shachter. Probabilistic Inference and Influence Diagrams , 1988, Oper. Res..
[27] Gregory F. Cooper,et al. KNET: integrating hypermedia and normative bayesian modeling , 1988, UAI.
[28] Ronald A. Howard. Uncertainty about Probability: A Decision Analysis Perspective , 1988 .
[29] Judea Pearl,et al. Probabilistic reasoning in intelligent systems , 1988 .
[30] Eric Horvitz,et al. Decision theory in expert systems and artificial intelligenc , 1988, Int. J. Approx. Reason..
[31] Ross D. Shachter. A linear approximation method for probabilistic inference , 2013, UAI.
[32] Samuel Holtzman,et al. Intelligent decision systems , 1988 .
[33] Chris Carter,et al. Multiple decision trees , 2013, UAI.
[34] Matthew Self,et al. Bayesian Classification , 1988, AAAI.
[35] P. Spirtes,et al. Latent variables, causal models and overidentifying constraints , 1988 .
[36] Alice M. Agogino,et al. Automated Construction of Sparse Bayesian Networks from Unstructured Probabilistic Models and Domain Information , 2013, UAI.
[37] Gregory F. Cooper,et al. Response to the discussion of the paper ‘current research directions in the development of expert systems based on belief networks’ , 1989 .
[38] Kevin T. Kelly,et al. Discovering Causal Structure. , 1989 .
[39] Max Henrion,et al. An Introduction to Algorithms for Inference in Belief Nets , 1989, UAI.
[40] Gregory F. Cooper,et al. Current research directions in the development of expert systems based on belief networks , 1989 .
[41] Douglas W. Nychka,et al. Discovering Causal Structure , 1989 .
[42] H. J. Suermondt,et al. Probabilistic Prediction of the Outcome of Bone-Marrow Transplantation , 1989 .
[43] Geoffrey E. Hinton. Connectionist Learning Procedures , 1989, Artif. Intell..
[44] Jaime G. Carbonell,et al. Introduction: Paradigms for Machine Learning , 1989, Artif. Intell..
[45] P. Spirtes,et al. Causality From Probability , 1989 .
[46] C. Robert Kenley,et al. Gaussian influence diagrams , 1989 .
[47] Gregory F. Cooper,et al. The ALARM Monitoring System: A Case Study with two Probabilistic Inference Techniques for Belief Networks , 1989, AIME.
[48] Stuart L. Crawford,et al. An architecture for probabilistic concept-based information retrieval , 1989, SIGIR '90.
[49] Judea Pearl,et al. Equivalence and Synthesis of Causal Models , 1990, UAI.
[50] Richard Scheines,et al. Simulation Studies of the Reliability of Computer-Aided Model Specification Using the TETRAD II, EQS, and LISREL Programs , 1990 .
[51] Dan Geiger,et al. Learning Causal Trees from Dependence Information , 1990, AAAI.
[52] P. Spirtes,et al. Causal structure among measured variables preserved with unmeasured variables , 1990 .
[53] Wray L. Buntine. Myths and Legends in Learning Classification Rules , 1990, AAAI.
[54] David Heckerman,et al. Probabilistic similarity networks , 1991, Networks.
[55] Richard E. Neapolitan,et al. Probabilistic reasoning in expert systems , 1990 .
[56] David J. Spiegelhalter,et al. Sequential updating of conditional probabilities on directed graphical structures , 1990, Networks.
[57] Stuart L. Crawford,et al. Constructor: A System for the Induction of Probabilistic Models , 1990, AAAI.
[58] Wray L. Buntine,et al. A theory of learning classification rules , 1990 .
[59] David Heckerman,et al. Advances in Probabilistic Reasoning , 1994, Conference on Uncertainty in Artificial Intelligence.
[60] P. Spirtes,et al. An Algorithm for Fast Recovery of Sparse Causal Graphs , 1991 .
[61] A. Mallet,et al. Learning probabilities in causal trees from incomplete databases , 1991 .
[62] Gregory F. Cooper,et al. A Bayesian Method for the Induction of Probabilistic Networks from Data , 1992 .
[63] Edward H. Herskovits,et al. Computer-based probabilistic-network construction , 1992 .
[64] Stuart L. Crawford,et al. An analysis of two probabilistic model induction techniques , 1992 .
[65] Ivan Bratko,et al. Machine learning in artificial intelligence , 1993, Artif. Intell. Eng..
[66] Shinichi Morishita,et al. On Classification and Regression , 1998, Discovery Science.
[67] Kathryn B. Laskey,et al. Uncertainty in Artificial Intelligence 15 , 1999 .
[68] J. Ross Quinlan,et al. Induction of Decision Trees , 1986, Machine Learning.
[69] Charles E. Heckler,et al. Applied Multivariate Statistical Analysis , 2005, Technometrics.