搜索资源列表
Pca-extraction
- PCA成分分析检测程序代码，运用MATLAB编写，能够很好分析主要特征-PCA component analysis testing program code, written using MATLAB, to analyze the main features of good
PCA-feature-extraction-and-SV-multi-class
- PCA特征抽取与SVM多类分类在传感器故障诊断中的应用PCA feature extraction and SVM multi-class classification in the sensor fault diagnosis-PCA feature extraction and SVM multi-class classification in the sensor fault diagnosis
PCA
- PCA算法。PCA的目的是找到能够分离出最大方差的方向，所以首先求原来所有数据三个维度上的协方差，然后求这个协方差的特征值，最大特征值为第一个方向，从此以此类推。-PCA algorithm. The purpose of PCA is to find able to isolate the direction of maximum variance, so first find all the data in three dimensions on the original covarianc
pca-matlab
- PCA又为主成分分析，是一种特征提取方法， 它通过线性变换寻找一组最优的单位正交向量基，用他们的线性组合来重构原样本-PCA and the main component analysis, a feature extraction method, which by finding a set of optimal linear transformation unit orthogonal base vectors, with their linear combination to recons
pca
- 主成分分析pca算法matlab程序代码：pca标准化、协方差、特征根特征向量、方差贡献率-Principal component analysis pca algorithm matlab code: pca standardized covariance, eigenvalues eigenvectors, the variance contribution rate. . .
pca
- 一个简单的用于人脸识别中PCA特征提取程序。-a simple PCA feature extraction program used in face recognition
palmprint-PCA
- 本程序是本人根据人脸识别PCA改进的，用于掌纹识别，是学习PCA特征提取的很好的学习资料。-I based this program is to improve the face recognition PCA for palmprint identification, PCA feature extraction is to learn a good learning materials.
PCA-and-SVM-Face-recognition
- 采用PCA对人脸特征进行抽取，用SVM多累分类器对人脸进行识别，有操作界面-Using PCA for facial feature extraction, and more tired with the SVM classifier for face identification, a user interface
PCA-extract-code
- PCA特征提取代码,对图像进行识别，并输出识别率，附详细说明-PCA characteristic extract code
PCA-based-facial-recognition
- 基于PCA特征提取和距离哈希K近邻分布的人脸表情识别-PCA-based feature extraction and distribution of K-nearest neighbor distance hash Facial Expression Recognition
K-Means PCA降维
- K-Means算法,不要求建立模型之后对结果进行新的预测，没有相应的标签，只是根据数据的特征对数据进行聚类。主成分分析降维对数据进行可视化操作,对features进行降维.(K-Means algorithm does not require the establishment of the model after the new prediction of the results, there is no corresponding tag, but only on the character
pca
- pca是主成分分析，提取特征，对数据进行降维处理(PCA is principal component analysis, which extracts features and processes the data in reduced dimension)
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
- Python实现PCA将数据转化成前K个主成分的伪码大致如下: ''' 减去平均数计算协方差矩阵计算协方差矩阵的特征值和特征向量将特征值从大到小排序保留最大的K个特征(Python PCA data into pseudo code before the K principal components are as follows: the characteristics of 'average minus the covariance matrix to calculate the covari
pca
- 用户可以选择/输入，减少数据集的特征数。(User can choose/input the no.of features in the reduced Dataset.)
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实现特征降维
- pca和_fase_pca实现特征降维，两种算法都有所改进，特别是pca可以根据自己的需要进行相应的改进，代码清晰易懂，希望对你有帮助。(PCA and _fase_pca to achieve feature reduction, the two algorithms have improved, especially PCA can be improved according to their needs, the code is clear and easy to understand,
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
- 非常经典的特征提取算法，经常用来做降维方法，但是也可以直接用来做特征提取，很适合图像处理入门，在人脸识别也经常用到(Very classic feature extraction algorithm, often used to do dimensionality reduction methods, but can also be used directly to do feature extraction, it is suitable for image processing, in fa
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)