Description: estimate the test accuracy,training accuray and validation accuracy of a neural network with 10-fold cross validation.-estimate the test accuracy,training accuray and validation accuracy of a neural network with 10-fold cross validation. Platform: |
Size: 1024 |
Author:sak |
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Description: The code implements a probabilstic Neuraol network for classification problems trained with a Leave One Out Cross Validation Scheme in Matlab (version 7 or above). The following toolboxes are required: statidtics, optimization and neural networks. Platform: |
Size: 33792 |
Author:Alfredo/Passos |
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Description: matlab交叉验证cross Validation，把样本集分为训练集和测试集，防止网络出现过拟合，提高网络的泛化能力和预测精度-cross Validation for matlab，to estimate the test accuracy,training accuray and validation accuracy of a neural network Platform: |
Size: 1024 |
Author:周杰伦 |
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Description: 神经网络训练，应用matlab7NN包，用一个隐藏层使用5折交叉验证。-Training the Neural Network
This script is something that I did for a course at Uni. It uses the Neural Networking package provided with MatLab 7 unfortunately I m not sure if it s available with the earlier versions of MatLab. This script uses the command lines for the package to perform the task, otherwise you can use the GUI that s provided, by typing nntool. This script shows 5 fold cross validation on a neural network with 1 hidden layer with a variable number of hidden nodes along with a single output. The entire process is done 2 times, because each time the data was encoded in a different manner, which in turn altered how much the Neural Network was able to learn from the data. Below you ll find the script to collect the data for the final results. Platform: |
Size: 2048 |
Author:kingking |
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Description: Grnn神经网络交叉验证，matlab中可实现代码文档-Grnn nerve network cross-validation, matlab in the can be to achieve the code documentation Platform: |
Size: 8192 |
Author:wujing |
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Description: 神经网络实例文件说明：
1. chapter26_lvq.m为主程序，将该文件夹设置为MATLAB当前工作路径，运行即可。
2. crossvalidation_lvq.mat为增加了交叉验证功能(确定最佳的隐含层神经元个数)的LVQ程序。
3. chapter26_bp.m为对比的BP程序。
4. data.mat为数据文件。
5. 该程序在MATLAB2009a版本下测试通过，个别函数在低版本中不存在或者调用格式有所不同，参照对应版本中的帮助文档修改即可。
-Examples of neural network file specifications:
1. chapter26_lvq.m main program, the folder is set to MATLAB current working directory, run it.
2. crossvalidation_lvq.mat to increase cross-validation (to determine the optimal number of neurons in the hidden layer) of LVQ program.
3. chapter26_bp.m contrast to BP for the program.
4. data.mat data file.
5. The program in MATLAB2009a version tested, the individual does not exist or function call format is different, with reference to the corresponding version of the revised document to help low version. Platform: |
Size: 90112 |
Author:LIULIU |
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Description: SURROGATES工具箱是一个多维函数逼近和优化方法的通用MATLAB库。当前版本包括以下功能：
实验设计：中心复合设计，全因子设计，拉丁超立方体设计，D-optimal和maxmin设计。
代理：克里金法，多项式响应面，径向基神经网络和支持向量回归。
错误和交叉验证的分析：留一法和k折交叉验证，以及经典的错误分析（确定系数，标准误差;均方根误差等;）。
基于代理的优化：高效的全局优化（EGO）算法。
其他能力：通过安全裕度进行全局敏感性分析和保守替代。(SURROGATES Toolbox is a general-purpose MATLAB library of multidimensional function approximation and optimization methods. The current version includes the following capabilities:
Design of experiments: central composite design, full factorial design, Latin hypercube design, D-optimal and maxmin designs.
Surrogates: kriging, polynomial response surface, radial basis neural network, and support vector regression.
Analysis of error and cross validation: leave-one-out and k-fold cross-validation, and classical error analysis (coefficient of determination, standard error; root mean square error; and others).
Surrogate-based optimization: efficient global optimization (EGO) algorithm.
Other capabilities: global sensitivity analysis and conservative surrogates via safety margin.) Platform: |
Size: 362496 |
Author:pluto1888 |
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