搜索资源列表
KPCAf
- KPCA算法，包括和函数的选择以及和矩阵的构造-PCA algorithms, and options include functions well and matrix structure, etc.
steven2358-kmbox-v0.11-0-g425fe66
- 核方法工具箱，包括核典型相关分析KCCA，KPLS等算法的源码和实现。-Kernel Methods Toolbox KMBOX includes implementations of algorithms such as kernel principal component analysis (KPCA), kernel canonical correlation analysis (KCCA) and kernel recursive least-squares (KRLS).
PhD
- 非常有用的人脸识别工具包，包含了各种PCA,LDA, KPCA, KFA及其变种。在Matlab环境下可以直接运行。-The PhD (Pretty helpful Development functions for) face recognition toolbox is a collection of Matlab functions and scr ipts intended to help researchers working in the field of face recognit
LBPpPCAp2CKPCAp2BSVM
- 人脸识别系统采用了LBP PCA 2CKPCA 2BSVM算法实现的，效率高。-Face Recognition System using LBP PCA 2B KPCA 2B SVM algorithm, and high efficiency.
KPCA
- 核主成分分析的MATLAB代码，欢迎使用-Kernel Principal Component Analysis MATLAB code, welcomed the use
特征降维
- 各种降维的方法，KPCA,KLDA,KLPP，应有尽有
PCA_kpca
- 利用pca和kpca对CSTR过程进行故障诊断，包括7个噪声及开环和串级控制-Pca for CSTR kpca use and process troubleshooting, including seven noise and open-loop and cascade control
aareition
- er than mean squared error (MSE) function only. As an additional merit, it is also revealed that rigorous Mercer kernel condition is not required in FKNN networks. When the proposed architecture of FKNN networks is constructed in a layer-by-lay
AKPCA
- 南京大学数据挖掘研究所提出的主动学习算法，对于改进KPCA有着重要的借鉴作用。-The active learning algorithm proposed data mining research institute of nanjing university, has an important reference for improving the KPCA.
Kpca
- 核主元分析法，将低维数据，映射到高维空间，进行更精确的非线性划分。-Kernel principal component analysis, the low-dimensional data, mapping to high-dimensional space for more accurate non-linear division.
KPCA
- 根据自己对于核主成分分析算法的理解，编程实现的MATLAB程序，如有理解不到位的地方，欢迎批评指正。-According to their own understanding of the analysis program MATLAB algorithms, programming for nuclear principal component, if understood not in place, welcome criticism.
kPCA-master
- 基于核的主成分分析是一种非线性特征提取方法,它通过一个非线性映射将数据从输入空间映射到特征空间,然后在特征空间中进行通常的主成分分析,其中的内积运算采用一个核函数来代替-Core-based principal component analysis is a nonlinear feature extraction method, which maps data the input space to the feature space through a nonlinear mapping,
yongyuceshiputaojiu
- 这是用于KPCA用于葡萄酒分类的测试代码。-Test code for KPCA for wine classification.
kpca1
- 作为多元数据的降维处理方法，有效减小数据的运算量。(As a dimension reduction method for multivariate data, the computation of data is effectively reduced.)
HMM(matlab函数集)
- hmm的matlab函数包，有需要的可以探讨交流。主要用于故障识别和预测。(HMM matlab function package, there is a need to explore the exchange. Mainly used for fault identification and prediction.)
KPCAomit
- 使用kpca方法进行特征提取，用作机器学习的第一步(Use kpca method for feature extraction, as the first step in machine learning)
kPCA_v3.1 (1)
- KPCA用于数据特征的降维，先通过核方法，将样本映射到高维空间，再进行主成分分析过程。(KPCA is used to reduce the dimension of data, first through the kernel method, the sample is mapped to high-dimensional space, and then the principal component analysis process.)
drtoolbox
- 包含多种常用维数优化算法及应用，PCA , ICA, LDA，LFA LPP，KPCA 等等。(There are many Dimensionality Reduction methods including PCA , ICA, KICA and so on.)
Demo
- PCA POUR REDUIRE LA TAILLE DES DONNEES ET APPLIAUER ENSUITE LA CLASSIFICATION AVEC LE KNN KDDCUP99 TRAININSET TESTINGSET
kpca1故障辨识
- 冶金工业过程中，选矿自动化过程中， 故障诊断、故障辨识。(Fault diagnosis and fault identification.)