In the past, expert systems exploited mainly the EMYCIN modeland the PROSPECTOR model to deal with uncertainties. In other words, a lot ofstand-alone expert systems which use these two models are available. If we can ...In the past, expert systems exploited mainly the EMYCIN modeland the PROSPECTOR model to deal with uncertainties. In other words, a lot ofstand-alone expert systems which use these two models are available. If we can usethe Internet to couple them together, their performance will be improved throughcooperation. This is because the problem-solving ability of expert systems is greatlyimproved by the way of cooperation among different expert systems in a distributedexpert system. Cooperation between different expert systems with these two het-erogeneous uncertain reasoning models is essentially based on the transformations ofuncertainties of propositions between these two models. In this paper, we discoveredthe exactly isomorphic transformations uncertainties between uncertain reasoningmodels, as used by EMYCIN and PROSPECTOR.展开更多
Mixture of Experts(MoE)regression models are widely studied in statistics and machine learning for modeling heterogeneity in data for regression,clustering and classification.Laplace distribution is one of the most im...Mixture of Experts(MoE)regression models are widely studied in statistics and machine learning for modeling heterogeneity in data for regression,clustering and classification.Laplace distribution is one of the most important statistical tools to analyze thick and tail data.Laplace Mixture of Linear Experts(LMoLE)regression models are based on the Laplace distribution which is more robust.Similar to modelling variance parameter in a homogeneous population,we propose and study a new novel class of models:heteroscedastic Laplace mixture of experts regression models to analyze the heteroscedastic data coming from a heterogeneous population in this paper.The issues of maximum likelihood estimation are addressed.In particular,Minorization-Maximization(MM)algorithm for estimating the regression parameters is developed.Properties of the estimators of the regression coefficients are evaluated through Monte Carlo simulations.Results from the analysis of two real data sets are presented.展开更多
文摘In the past, expert systems exploited mainly the EMYCIN modeland the PROSPECTOR model to deal with uncertainties. In other words, a lot ofstand-alone expert systems which use these two models are available. If we can usethe Internet to couple them together, their performance will be improved throughcooperation. This is because the problem-solving ability of expert systems is greatlyimproved by the way of cooperation among different expert systems in a distributedexpert system. Cooperation between different expert systems with these two het-erogeneous uncertain reasoning models is essentially based on the transformations ofuncertainties of propositions between these two models. In this paper, we discoveredthe exactly isomorphic transformations uncertainties between uncertain reasoningmodels, as used by EMYCIN and PROSPECTOR.
基金the National Natural Science Foundation of China(11861041,11261025).
文摘Mixture of Experts(MoE)regression models are widely studied in statistics and machine learning for modeling heterogeneity in data for regression,clustering and classification.Laplace distribution is one of the most important statistical tools to analyze thick and tail data.Laplace Mixture of Linear Experts(LMoLE)regression models are based on the Laplace distribution which is more robust.Similar to modelling variance parameter in a homogeneous population,we propose and study a new novel class of models:heteroscedastic Laplace mixture of experts regression models to analyze the heteroscedastic data coming from a heterogeneous population in this paper.The issues of maximum likelihood estimation are addressed.In particular,Minorization-Maximization(MM)algorithm for estimating the regression parameters is developed.Properties of the estimators of the regression coefficients are evaluated through Monte Carlo simulations.Results from the analysis of two real data sets are presented.
