代码搜索：Bayesian
找到约 1,632 项符合「Bayesian」的源代码
代码结果 1,632
www.eeworm.com/read/305450/13769565
m torr_mapsac_f.m
% By Philip Torr 2002
% copyright Microsoft Corp.
%MAPSAC is the Bayesian version of MLESAC, and it is easier to pronounce!
%
% %designed for the good of the world by Philip Torr based on ideas c
www.eeworm.com/read/305450/13769574
m torr_napsac_f.m
% By Philip Torr 2002
% copyright Microsoft Corp.
%MAPSAC is the Bayesian version of MLESAC, and it is easier to pronounce!
%
% %designed for the good of the world by Philip Torr based on ideas c
www.eeworm.com/read/485544/6552829
m contents.m
% ReBEL : Recursive Bayesian Estimation Library - Toolkit
% Version 0.2
%
% ---CORE ROUTINES---
%
% ReBEL Inference System Routines
% consistent - Check ReBEL data structures for consisten
www.eeworm.com/read/343227/11962832
m ex_bic.m
%ex_bic Example of cluster analysis with varying number of mixture
% components using the BIC (Bayesian Information Criterion) to assess
% the fit provided by mixture model of dif
www.eeworm.com/read/220289/14843971
m contents.m
% ReBEL : Recursive Bayesian Estimation Library - Toolkit
% Version 0.2
%
% ---CORE ROUTINES---
%
% ReBEL Inference System Routines
% consistent - Check ReBEL data structures for consisten
www.eeworm.com/read/12816/246885
m torr_mapsac_f.m
% By Philip Torr 2002
% copyright Microsoft Corp.
%MAPSAC is the Bayesian version of MLESAC, and it is easier to pronounce!
%
% %designed for the good of the world by Philip Torr based on ideas c
www.eeworm.com/read/12816/246894
m torr_napsac_f.m
% By Philip Torr 2002
% copyright Microsoft Corp.
%MAPSAC is the Bayesian version of MLESAC, and it is easier to pronounce!
%
% %designed for the good of the world by Philip Torr based on ideas c
www.eeworm.com/read/429426/1948659
py fss4.py
# Description: Demonstrates the use of orngFSS.FilteredLearner to compare
# naive Bayesian learner when all or just the most important attribute
# is used. Shows how to fin
www.eeworm.com/read/359369/2978580
m contents.m
% ReBEL : Recursive Bayesian Estimation Library - Toolkit
% Version 0.2
%
% ---CORE ROUTINES---
%
% ReBEL Inference System Routines
% consistent - Check ReBEL data structures for consisten
www.eeworm.com/read/393436/8287403
m impsampdemo.m
%This is a simple demonstration of the approximate method for GP based
%classification over multiple classes which is presented in
%
% Girolami, M., Rogers, S.,
% Variational Bayesian Multinomial