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: 43008 |
Author:吴成 |
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Description: 关于图像配准中的交叉相关的实现，可以直接调用。-About Image Registration in the implementation of cross-correlation can be directly called. Platform: |
Size: 5120 |
Author:sai |
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Description: 图像分类中的交叉验证方法，比如说，一个训练集集合，为了得到其中参数的较准确值，就可以使用此类算法-Image Classification Based on cross-validation method, for example, a collection of training set, in order to obtain more accurate values of these parameters, you can use these algorithms Platform: |
Size: 1024 |
Author:苏晓蕾 |
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Description: LIBSVM是台湾大学林智仁(Lin Chih-Jen)副教授等开发设计的一个简单、易于使用和快速有效的SVM模式识别与回归的软件包，他不但提供了编译好的可在Windows系列系统的执行文件，还提供了源代码，方便改进、修改以及在其它操作系统上应用；该软件还有一个特点，就是对SVM所涉及的参数调节相对比较少，提供了很多的默认参数，利用这些默认参数就可以解决很多问题；并且提供了交互检验(Cross Validation)的功能。-LIBSVM Taiwan University, Lin Zhiren (Lin Chih-Jen) and associate development and design of a simple, easy to use and fast and efficient SVM pattern recognition and regression of the package, he can not only provide a compiled implementation of the system in the Windows family of documents , also provides the source code to facilitate the improvement, modification and other operating systems applications the software has a feature that the parameters of the SVM involves relatively small adjustment to provide a lot of default parameters, use the default parameters on can solve many problems and to provide a cross-validation (Cross Validation) feature. Platform: |
Size: 472064 |
Author:朱业林 |
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Description: 寻找相应的特点,在一副图片的基础是许多光流、立体的视觉和图像间的配准算法。一个发现匹配方法简单,取一小块一个图像,计算其滑动互相与其他的形象,并找到一个高峰。此表格提供了课堂的实现方法。-Finding corresponding features in a pair of images is the basis of many optic flow, stereo vision and image registration algorithms. One straightforward approach to finding a match is to take a small patch of one image, compute its sliding cross-correlation with the other image, and find a peak. This submission supplies a class which implements this method.
Platform: |
Size: 776192 |
Author:王羽 |
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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: 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: 嵌入维数自适应最小二乘支持向量机
状态时间序列预测方法
Condition Time Series Prediction Using Least Squares Support Vector Machine
with Adaptive Embedding Dimension
针对航空发动机状态时间序列预测中嵌入维数难于有效选取的问题, 提出一种基于嵌入维数自适应
最小二乘支持向量机( L SSVM ) 的预测方法。该方法将嵌入维数作为影响状态时间序列预测精度的重要参
数, 以交叉验证误差为评价准则, 利用粒子群优化( P SO ) 进化搜索LSSV M 预测模型的最优超参数与嵌入维
数, 同时通过矩阵变换原理提高交叉验证过程的计算效率, 并最终建立优化后的L SSVM 预测模型。航空发
动机排气温度( EGT ) 预测实例表明, 该方法可自适应选取适用于状态时间序列预测的最优嵌入维数且预测
精度高, 适用于航空发动机状态时间序列预测。- T o deal wit h the difficulty of selecting an appro pr iate embedding dimension for aeroeng ine co ndition
time series predictio n, a metho d based o n least squar es suppo rt vecto r machine ( L SSVM ) with ada ptive em
bedding dimension is pro po sed. I n the method, the embedding dimensio n is identified as a parameter that af
fects the accuracy o f the aer oengine condition time series predictio n par ticle sw arm o ptimizat ion ( P SO) is ap
plied to optimize the hyperpar ameter s and embedding dimension of the L SSV M pr edict ion model cro ssv alida
tion is applied to evaluate the perfo rmance o f the L SSVM predictio n mo del and matr ix tr ansfo rm is applied to
the L SSVM pr ediction model tr aining to accelerate the crossvalidation evaluation pro cess. Ex periments on an
aeroengine ex haust g as t emperatur e ( EGT ) predictio n demonst rates that the metho d is hig hly effective in em
bedding dimension selection. In compar ison w ith co nv Platform: |
Size: 342016 |
Author: |
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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: 用matlab实现Part1. 实现一个k近邻分类器，Part 2.实现一个最小二乘分类器，Part 3.实现一个支持向量机分类器，Part 4.在不同数据集上使用交叉验证选择各个算法的参数-Part1. Achieve a k-nearest neighbor classifier, Part 2. Achieve a least-squares classifier, Part 3. Implement a support vector machine classifier, Part 4. Different data sets used in the cross-validation to select individual parameters of the algorithm Platform: |
Size: 4096 |
Author:张翰晓 |
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Description: 与其它高级语言相比较，MATLAB具有独特的优势：(1) MATLAB是一种跨平台的数学语言。(2) MATLAB是一种超高级语言。MATLAB平台本身是用C语言写成的，所以在编程效率，程序的可读性、可靠性和可移植性上远远超过了常规的高级语言。(3) MATLAB语法简单，编程风格接近数学语言描述，是数学算法开发和验证的最佳工具。(4) MATLAB计算精度很高。与其它语言相比，MATLAB对计算机内存、硬盘空间的要求也是比较高的。-Compared with other high-level languages , MATLAB has unique advantages: (1) MATLAB is a cross-platform language of mathematics. (2) MATLAB is a super-high-level language. MATLAB platform itself is written in C, so the programming efficiency, readability, reliability and portability far more than the regular high-level language. (3) MATLAB syntax is simple, close to the mathematical language to describe the style of programming is a mathematical algorithm development and validation of the best tools. (4) MATLAB computing high accuracy. Compared with other languages , MATLAB computer memory, disk space requirements are relatively high. Platform: |
Size: 3441664 |
Author:zn |
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Description: 该压缩包主要是关于lasso的matlab程序，其中包含lasso的code,lasso在例子中的应用，以及lemda的交叉验证等。-The archive is mainly about lasso matlab program, which includes lasso the code, lasso in the example application, as well as cross-validation lemda like. Platform: |
Size: 5782528 |
Author:swan |
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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: 输入一组数据，从从中随机把样本分为测试数据与验证数据(Random selection of samples from cross validation in a set of access data) Platform: |
Size: 9216 |
Author:even_1
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Description: 采用10折交叉验证得到光合速率预测模型，代码中有程序语言的详细注释。(The 90% off cross validation of photosynthetic rate prediction model, the procedures detailed notes in the language code.) Platform: |
Size: 1024 |
Author:fsdfsdfsdfsd
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Description: 本程序为广义交叉验证（GCV）的matlab代码，在一些场合有比交叉验证（OCV）更好的特性(This program is a generalized cross validation (GCV) matlab code, in some cases than cross validation (OCV) better characteristics) Platform: |
Size: 1024 |
Author:lzu666 |
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Search - cross validation in matlab