Location:
Search - Model Selection
Search list
Description: PCF8563 的驱动程序，用两个普通的IO口模拟I2C总线，包括100KHZ（T=10US）的标准模式选择和400KHZ的快速模式选择，默认11.0592MHZ的晶振-PCF8563 of the driver, with two ordinary analog IO I2C bus, including the extremely low distortion (T = 10US), the standard model selection and 400KHZ fast mode selection, the crystal default 11.0592MHZ
Platform: |
Size: 83450 |
Author: yk1861 |
Hits:
Description: Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It can solve C-SVM classification,
nu-SVM classification, one-class-SVM, epsilon-SVM regression, and
nu-SVM regression. It also provides an automatic model selection
tool for C-SVM classification. This document explains the use of
libsvm.
-Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It can solve C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM classification. This document explains the use of libsvm.
Platform: |
Size: 461950 |
Author: 陈中 |
Hits:
Description: New in this version:
Support for multi-class pattern recognition using maxwins, pairwise [4] and DAG-SVM [5] algorithms.
A model selection criterion (the xi-alpha bound [6,7] on the leave-one-out cross-validation error).
-New in this version : Support for multi-class pattern recognition u maxwins sing, Pairwise [4] and DAG - SVM [5] algorithms. A mode l selection criterion (the xi-alpha bound [6, 7] on the leave-one-out cross-validation erro r).
Platform: |
Size: 43182 |
Author: 吴成 |
Hits:
Description: This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima. It allows the user to choose among various model selection criteria, including AIC, BIC and MDL
Platform: |
Size: 958327 |
Author: 郭剑辉 |
Hits:
Description: Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic model selection tool for
C-SVM classification. This document explains the use of libsvm.
-Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classificatio n, nu-SVM classification, one-class-SVM. epsilon - SVM regression. and nu-SVM regression. It also provides an auto matic model selection tool for C-SVM classific ation. This document explains the use of libsvm .
Platform: |
Size: 7900 |
Author: pangjiufeng |
Hits:
Description: 该程序为基于粒子滤波的一种新算法,综合MCMC Bayesian Model Selection即MONTE CARLO马尔克夫链的算法,用来实现目标跟踪,多目标跟踪,及视频目标跟踪及定位等,解决非线性问题的能力比卡尔曼滤波,EKF,UKF好多了,是我珍藏的好东西,现拿出来与大家共享,舍不得孩子套不着狼,希望大家相互支持,共同促进.-the program based on particle filter for a new algorithm, Integrated Bayesian MCMC Model Selection MONTE CARLO that Ma Erkefu chain algorithm, which can be used for target tracking, multi-target tracking, and video tracking and positioning. solve nonlinear problems of capacity than Kalman filtering, EKF, UKF much better, and I treasure the good stuff, now up with the share could not bear children, she sets the wolf, we hope that support each other and work together to promote.
Platform: |
Size: 14805 |
Author: zhang |
Hits:
Description: 本文介绍了医学信号分析的常用方法，着重介绍了神经网络模式识别，包括他的优点及不足，最后介绍了神经网络的模型选择。-medical signal analysis methods commonly used to highlight the neural network pattern recognition, including his strengths and weaknesses, and the final presentation to the neural network model selection.
Platform: |
Size: 9657 |
Author: 王东 |
Hits:
Description: Bayesian Model Selection
Platform: |
Size: 3177 |
Author: 李川风 |
Hits:
Description: Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It can solve C-SVM classification,
nu-SVM classification, one-class-SVM, epsilon-SVM regression, and
nu-SVM regression. It also provides an automatic model selection
tool for C-SVM classification. This document explains the use of
libsvm.
-Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It can solve C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM classification. This document explains the use of libsvm.
Platform: |
Size: 461824 |
Author: 陈中 |
Hits:
Description: This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima. It allows the user to choose among various model selection criteria, including AIC, BIC and MDL
Platform: |
Size: 958464 |
Author: 大辉 |
Hits:
Description: gaussian algorithm for Bayesian Model Selection
Platform: |
Size: 1024 |
Author: 李川风 |
Hits:
Description: On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
-On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar-xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
Platform: |
Size: 16384 |
Author: 徐剑 |
Hits:
Description: This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.-This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar-xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
Platform: |
Size: 220160 |
Author: 晨间 |
Hits:
Description: libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic model selection tool for
C-SVM classification. This document explains the use of libsvm.
Platform: |
Size: 295936 |
Author: baolij |
Hits:
Description: Bayes model averaging with selection of regressors - This program can be utilized for Bayesian Variable Selection using Gibbs Sampler-Bayes model averaging with selection of regressors- This program can be utilized for Bayesian Variable Selection using Gibbs Sampler
Platform: |
Size: 9216 |
Author: Ruo Wang |
Hits:
Description: The BYY annealing learning algorithm for Gaussian mixture with automated model selection
Platform: |
Size: 870400 |
Author: anie |
Hits:
Description: svm model selection by pso
Platform: |
Size: 746496 |
Author: ngu |
Hits:
Description: 主要介绍机器学习中的规则化和模型选择(Regularization and model selection)-Regularization and model selection
Platform: |
Size: 743424 |
Author: dsds |
Hits:
Description: bayes factor for model selection
Platform: |
Size: 257024 |
Author: Shamohammadi |
Hits:
Description: bayesian model selection among dfferent models
Platform: |
Size: 309248 |
Author: Shamohammadi |
Hits:
« 12
3
4
5
6
7
8
9
10
...
21
»