Description: Matlab source codes for the regularized linear discriminant analysis (R-LDA)，Author: Lu Juwei，Bell Canada Multimedia Lab, Dept. of ECE, U. of Toronto，Released in 01 November 2004 -Matlab source codes for the regularized linear discriminant analysis (R-LDA), Author: Lu Juwei, Bell Canada Multimedia Lab, Dept. Of ECE, U. of Toronto, Released in 01 November 2004 Platform: |
Size: 652288 |
Author:qiuzhihao |
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Description: 这个程序实现了Francis R. Bach的Bolasso算法，用于特征选取和预测。主要用于高纬度问题的特征选取，它使用了带有Bootstrap方法的自助抽样的正则化回归，并使用了Karl Skoglund的lars实现。-This procedure achieved Francis R. Bach s Bolasso algorithms for feature selection and forecasting. The main problem for high-latitude feature selection, it uses a method of self-help Bootstrap sampling Tikhonov reunification, and Karl Skoglund used to achieve the lars. Platform: |
Size: 198656 |
Author:xuechaoling |
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Description: 用遗传算法进行特征选取和svm参数优化的程序。遗传算法工具箱goat已在压缩包 需要安装libsvm就可以直接运行。数据集采用UCI中的german数据集，并完成归一化操作-Genetic algorithm with feature selection and parameter optimization svm procedures. Genetic Algorithm Toolbox in goat need to install libsvm package can be run directly. UCI data sets used in the german data set, and complete normalization operation Platform: |
Size: 139264 |
Author:覃茂运 |
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Description: mRMR_0.9_compiled最小冗余和最大相关特征选取源代码，-This package is the mRMR (minimum-redundancy maximum-relevancy) feature selection method, whose better performance over the conventional top-ranking method has been demonstrated on a number of data sets in recent publications. This version uses mutual information as a proxy for computing relevance and redundancy among variables (features). Other variations such as using correlation or F-test or distances can be easily implemented within this framework, too.
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Size: 1020928 |
Author:韩华 |
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Description: K-meansK均值聚类在无监督的情况下选择图像特征的算法-K-meansK means clustering in the case of unsupervised image feature selection algorithm Platform: |
Size: 46080 |
Author:renli |
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Description: ：将信息论中熵的概念应用到特征选择中，定义了两种信息测度评价特征——误差熵和混叠熵，然后阐述了两种定义的不
用物理意义，分析了计算熵中最关键的区间划分问题，并提出一种较好的区间划分方法。-: The concept of entropy in information theory applied to feature selection, the definition of information measure evaluation of two features- error entropy and mixing entropy, and then describes the two definitions do not have the physical meaning of the calculation of entropy in the range of the most critical partitioning problem and propose a better method of interval division. Platform: |
Size: 287744 |
Author:wangcong |
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Description: 粗糙集代码
data reduction with fuzzy rough sets or fuzzy mutual information
fuzzy preference rough set based feature evaluation and selection
-Rough code data reduction with fuzzy rough sets or fuzzy mutual information fuzzy preference rough set based feature evaluation and selection Platform: |
Size: 38912 |
Author:gq |
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Description: Kuschner论文，贝叶斯网络方法在质谱数据特征选择。其中关于机器学习中贝叶斯分类器部分有完整原理分析，可以用于认知无线电网络的频谱感知等新领域。含有matlab程序大于100页，子函数很多。-Kuschner paper, Bayesian network methods of feature selection in mass spectrometry data. One of the Bayes classifier machine learning part of a complete theory analysis, can be used for spectrum sensing cognitive radio networks and other new fields. Matlab program contains more than 100 pages, Functions a lot. Platform: |
Size: 2061312 |
Author:孟庆民 |
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Description: 特征选择算法，效果很好。可以解决维数高、训练样本数少的问题。-include both C version (mex-function) and Matlab version:
SBSVM_c.cc
SBSVM_m.m
A testing case is also provided in file Speed_Comp.m
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Size: 153600 |
Author:刘阳 |
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Description: This submission contains
(1) Journal Article on Zernike Moments, Genetic Algorithm, Feature Selection and Probabilistic Neural Networks.
(2) MATLAB code to do Feature Selection Using Genetic Algorithm.
NB:
(i) This code is short BUT it works incredibly well since we employed GA Toolbox.
(ii) You can run this code directly on your computer since the dataset herein is available in MATLAB software.
(iii) Please do cite my publication to give credit to me (if you use this code).
The citation is as follows:
BABATUNDE Oluleye, ARMSTRONG Leisa J, LENG Jinsong and DIEPEVEEN Dean (2014). Zernike Moments and Genetic Algorithm: Tutorial and Application. British Journal of Mathematics & Computer Science. 4(15):2217-2236.
Or
BABATUNDE, Oluleye and ARMSTRONG, Leisa and LENG, Jinsong and DIEPEVEEN (2014). A Genetic Algorithm-Based Feature Selection. International Journal of Electronics Communication and Computer Engineering: 5(4) 889 905.-This submission contains
(1) Journal Article on Zernike Moments, Genetic Algorithm, Feature Selection and Probabilistic Neural Networks.
(2) MATLAB code to do Feature Selection Using Genetic Algorithm.
NB:
(i) This code is short BUT it works incredibly well since we employed GA Toolbox.
(ii) You can run this code directly on your computer since the dataset herein is available in MATLAB software.
(iii) Please do cite my publication to give credit to me (if you use this code).
The citation is as follows:
BABATUNDE Oluleye, ARMSTRONG Leisa J, LENG Jinsong and DIEPEVEEN Dean (2014). Zernike Moments and Genetic Algorithm: Tutorial and Application. British Journal of Mathematics & Computer Science. 4(15):2217-2236.
Or
BABATUNDE, Oluleye and ARMSTRONG, Leisa and LENG, Jinsong and DIEPEVEEN (2014). A Genetic Algorithm-Based Feature Selection. International Journal of Electronics Communication and Computer Engineering: 5(4) 889 905. Platform: |
Size: 1434624 |
Author:abdalla |
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Search - feature selection in matlab