Search - KPCA data reduction

Search - KPCA data reduction - List

[Special Effects] KPCA DL : 0: 一个很好的PCA程序。它可用于数据的降维，消噪及特征提取。-A good PCA procedures. It can be used for data dimensionality reduction, de-noising and feature extraction.
Update : 2025-02-17 Size : 2kb Publisher : xiaolinzi
[AI-NN-PR] kpca081223 DL : 0: 非线性降维方法KPCA 可以应用于高维数据的机器学习-KPCA nonlinear dimensionality reduction methods can be applied to high-dimensional data, machine learning
Update : 2025-02-17 Size : 1kb Publisher : 王博
[Other] kpcaprogram DL : 1: 核主元分析程序，本人毕业设计程序，用于降维，监测Te过程故障，误诊断率低。-KPCA program, I graduated from the design process for dimension reduction, monitoring Te process failure, error diagnosis rate is low.
Update : 2025-02-17 Size : 12kb Publisher : 石怀涛
[matlab] KPCA00 DL : 0: kpca原始程序和小波去噪部分，用于数据降维和特征提取比较实用-kpca part of the original program and wavelet denoising for data dimensionality reduction and feature extraction more practical
Update : 2025-02-17 Size : 2kb Publisher : 杨武
[matlab] Fault7_KPCA0 DL : 0: KPCA程序，可用于数据降维，特征提取，用起来比较简单-KPCA procedure can be used for data dimensionality reduction, feature extraction, using relatively simple
Update : 2025-02-17 Size : 1kb Publisher : 杨武
[Windows Develop] KPCA DL : 0: 本方法使用sprtool，介绍了Kpca的应用，来进行高位数据降维，介绍三种核函数的应用，并附有结果图。-This method uses sprtool, introduced Kpca applications for high data dimensionality reduction, introduced three nuclear function, together with the results in Fig.
Update : 2025-02-17 Size : 64kb Publisher : candy
[Special Effects] kpcacsdn DL : 0: kpca的算法实现源码，实现了一个数据降维方面的经典算法kpca-kpca the algorithm source code, to achieve a data dimensionality reduction classical algorithm kpca
Update : 2025-02-17 Size : 1kb Publisher : 韩江
[Special Effects] kpca_toy DL : 0: kpca的算法实现源码，实现了一个数据降维方面的经典算法kpca-kpca the algorithm source code, to achieve a data dimensionality reduction classical algorithm kpca
Update : 2025-02-17 Size : 1kb Publisher : 韩江
[Special Effects] dimen_toolbox DL : 1: 最新最强MATLAB降维工具箱，可用于人脸识别，模式识别，机器学习，数据挖掘，图像处理等领域，里面包含的算法有PCA,LDA,KPCA,KLDA,Laplacian，LPP,MDS,NPE,SPE,LLC,CFA,MCML,LM-The latest and greatest dimension reduction MATLAB toolbox can be used for face recognition, pattern recognition, machine learning, data mining, and other areas of image processing, which contains the algorithm PCA, LDA, KPCA, KLDA, Laplacian, LPP, MDS, NPE, SPE, LLC, CFA, MCML, LMNN etc.
Update : 2025-02-17 Size : 1018kb Publisher : FDX
[matlab] kpca DL : 0: 核主元分析程序,基于主元分析进行开发编写，可实现核空间数据降维-KPCA program developed to prepare based on principal component analysis, nuclear spatial data dimensionality reduction
Update : 2025-02-17 Size : 6.08mb Publisher : 李婷
[Special Effects] kpca-ecg DL : 1: 对心电信号QRS波的数据降维，已经把QRS波截取出来-QRS wave of ECG data dimensionality reduction
Update : 2025-02-17 Size : 8kb Publisher : 王月霞
[DataMining] mani DL : 0: 此代码是关于流形学习，数据降维，代码中含有的主要方法是PCA，KPCA，MDS，KMDS，Laplacian等等，且代码作了可视化处理，界面效果完美-This code is on the manifold learning, data dimensionality reduction, the main method code is contained in PCA, KPCA, MDS, KMDS, Laplacian, etc., and the code visualization made perfect interface effects
Update : 2025-02-17 Size : 14kb Publisher : 张陈
[AI-NN-PR] kpca DL : 0: 在matlab上面通过kpca，实现大数据降维算法(Dimensionality reduction algorithm for large data)
Update : 2025-02-17 Size : 1kb Publisher : hi_blog
[matlab] kpca1 DL : 0: 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.)
Update : 2025-02-17 Size : 1kb Publisher : 康瑞五秒1
[Special Effects] kPCA DL : 0: 实现kPCA算法，用于数据降维图像处理等多领域。本程序包可选用多种核函数，且可以直接增添新的数据点，方便快捷。(KPCA algorithm, for data reduction, image processing and many other fields. This package can use a variety of kernel functions, and can directly add new data points, convenient and quick.)
Update : 2025-02-17 Size : 5kb Publisher : huagliu
[matlab] KPCA DL : 0: KPCA算法属于非线性高维数据集降维，算法其实很简单，数据在低维度空间不是线性可分的，但是在高维度空间就可以变成线性可分的了(The KPCA algorithm belongs to the nonlinear high-dimensional data set dimension reduction. The algorithm is very simple. The data is not linearly separable in the low-dimensional space, but can be linearly separable in the high-dimensional space.)
Update : 2025-02-17 Size : 59kb Publisher : 小轩5837