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程序
- 模式识别在MATLAB程序下的有关算法程序,包括Fisher分类,ML分类,parzen窗分类,直方图画法,roc曲线,roc分类等(Pattern recognition in the MATLAB program related algorithm program, including Fisher classification, ML classification, Parzen window classification, histogram drawing, ROC curve, RO
FDDL_IJCV
- Fisher discriminant dictionary learning approach for face recognition
5107533
- 利用fisher线性判别分析进行数据降维()
vmawin-12.081a
- This small utility allows you to list, extract, and/or create VMARC archive files. It is currently maintained by Ross Patterson, and VMARC was originally written by John Fisher.
feature_rank-master
- 这个函数计算费舍得分或特征的鉴别系数。 它可以用于两类功能选择场景。(This function computes the Fisher Score or Discriminating Coefficient of features. It can be used in two class feature selection scenarios.)
FS
- 该代码可对数据进行特征筛选,得到的结果为所选中特征的序列号,很好用哒,有啥问题大家一起留言交流呀(The code can select the characteristics of the data, the result is the sequence number of the selected features, which is very useful.)
fisherT
- 一段用于数据分类,分级的费舍尔判别分析算法,MATLAB代码(A Fisher discriminant analysis algorithm for data classification and classification, MATLAB code)
feature-selection-master
- 最小冗余最大相关性(MRMR)(MRMR.M) 需要外部库。详情请见MRMR。下载一个更新版本的互信息工具箱 偏最小二乘(PLS)回归系数(ReGCOEF.m) 使用MATLAB统计工具箱中的PLSReress ReliefF(分类)和RReliefF(回归)(ReleFracePr.M.) 从Matlab STATS工具箱中包装Releff.m。这是Matlab R2010B以后提供的。 ReliefF的另一个选择是使用ASU特征选择工具箱中的代码。这使用WEKA
fisher
- 识别所给出图像与图像库中的图像进行比对识别分类(The recognition and classification of the image and the image in the image library are identified.)
SFB_matlab1.0.tar
- 3D点云重建 3D点云重建Berkeley SfM is a structure from motion library created to explore new solutions to challenging 3D reconstruction problems (large scale, indoors, incremental, homogeneously textured, etc.). It is developed by(Structrue From Motion for
Find the best tree for Fisher
- 随机森林是一大算法,这个程序是随机森林中的一个小例子的展示。(Random forest is a large algorithm. This program is a demonstration of a small example in random forests.)
iris_data
- Iris Data Set(鸢尾属植物数据集)是我现在接触到的历史最悠久的数据集,它首次出现在著名的英国统计学家和生物学家Ronald Fisher 1936年的论文《The use of multiple measurements in taxonomic problems》中,被用来介绍线性判别式分析。在这个数据集中,包括了三类不同的鸢尾属植物:Iris Setosa,Iris Versicolour,Iris Virginica。每类收集了50个样本,因此这个数据集一共包含了150个样本。
FDDL
- 基于Fisher字典学习的稀疏表示分类算法。(Sparse representation classification algorithm based on Fisher dictionary learning.)
34节点随机潮流计算
- 34节点随机潮流计算:包括半不变量法和蒙特卡洛法的对比分析,其中半不变量法对应两种级数展开的方式:Gram Charlier和Cornish Fisher
鸢尾花分类
- 使用四种方法进行鸢尾花分类:最小距离分类器,K 近邻法,感知器,Fisher 准则。(Four methods are used to classify iris: minimum distance classifier, K-nearest neighbor method, perceptron and Fisher criterion.)
LDA
- 使用fisher线性判别函数对iris与sonar数据集进行分类(Using Fisher linear discriminant function to classify iris and sonar datasets)
基于核主元分析的非线性过程监测与诊断研究
- 图像分类,Fisher判别式,贡献图图像分类,Fisher判别式,贡献图图像分类,Fisher判别式,贡献图图像分类,Fisher判别式,贡献图
DIGITAL BEAMFORMING
- DIGITAL BEAMFORMING version 1.0.0.0 (2.77 KB) by King Fisher plots the beam pattern of antenna arrays.