搜索资源列表
pca
- matlab下主程序分析pca代码模板,可以直接使用。(Matlab under the main program analysis, PCA code template, you can use directly.)
pca
- princa,用于pca主成分降维:计算第k主成份贡献率-累计贡献率-取累计贡献率大于等于90%的主成分(For PCA principal component dimensionality reduction: calculate the principal component contribution rate of K - the cumulative contribution rate - take the cumulative contribution rate greater tha
pca降维
- pca数据降维算法,很好的解决数据灾难的问题。(PCA data dimensionality reduction algorithm, a good solution to the problem of data disaster.)
pca计算
- 基 于 matlab 的pca程序,挺不错的(PCA matlab program, pretty good)
PCA
- PCA主成分分析算法matlab源码,利用matlab实现PCA算法。(PCA principal component analysis algorithm matlab source code, using MATLAB to achieve PCA algorithm.)
PCA
- 主成分分析(Principal Component Analysis,PCA), 是一种统计方法。通过正交变换将一组可能存在相关性的变量转换为一组线性不相关的变量,转换后的这组变量叫主成分。(Principal Component Analysis (PCA) is a statistical method. Convert a set of variables that may be relevant by orthogonal transform into a set of linearly
PCA
- PCA算法的matlab实现及算例,包含原始数据(matlab code of PCA in machine learning)
PCA
- PCA在故障诊断中的应用,故障诊断所需要的数据,运行可得到他的T2和SPE(The application of PCA in fault diagnosis and the data needed for fault diagnosis)
pca
- PCA原理源代码,MATLAB程序仿真实验(the simulation experiment of PCA,MATLAB)
PCA
- PCA主成分分析,提取主特征,降维处理(PCA principal component analysis is used to extract the main features and reduce the dimensionality)
PCA
- 简单的数据降维算法(PCA)举例,构造随机的10维数据,降维成3维的。Sample可替换成用户数据(Examples of simple data reduction algorithms (PCA) are presented)
Nonlinear PCA toolbox for MATLAB
- 压缩文件夹中主要包含用于非线性主成分分析的程序(Nonlinear PCA toolbox for MATLAB)
MNIST-PCA
- 使用PCA算法分析MNIST 手写字符训练样本。 结果分别生成以2、5、10个PCA主成分的重构图像以及10个主成分特征向量的对应图像。(Implement PCA algorithm on MNIST dataset and calculate the class PCA on each digit separately.)
PCA-SVM-master
- PCA/SVM算法实现图像分类,分类准确率可到达90%(Image classification by PCA/SVM algorithm)
PCA笔记
- 对PCA的个人理解,有详细的PCA推导过程,代码包括计算协方差,及其特征值特征向量。(For the personal understanding of PCA, there is a detailed process of PCA derivation. The code includes the calculation covariance and its eigenvalue eigenvector.)
PCA
- PCA 算法演示 主要用于数据进行降维处理(PCA suanfa zhuyaoyongyushujujinxingjiangweichuli)
PCA
- 采用INP数据(145*145*200),该数据有16个类别, PCA进行数据降维,然后对降维数据采用kNN分类(k=1)。(Using INP data (145*145*200), the data has 16 categories, PCA carries out data reduction, and then uses kNN classification for dimensionality reduction data (k=1).)
PCA故障诊断步骤
- PCA故障分析程序,主元分析法,故障诊断,TE过程的数据。(PCA fault analysis program, principal component analysis, fault diagnosis, TE process data.)
pca算法实现
- 通过Python实现了PCA数据降维的方法(The method of reducing the dimension of PCA data through Python)
PCA-master
- PCA降维 无监督特征提取 参考文献:Paper used - http://cs229.stanford.edu/notes/cs229-notes10.pdf(PCA # PCA - Unsupervised feature extraction technique Paper used - http://cs229.stanford.edu/notes/cs229-notes10.pdf)