搜索资源列表
66lle
- LLE降维的源码，内有详细说明，供初学者学习-LLE dimensionality reduction of the source, with detailed instructions for beginners to learn
PCA
- 应用PCA进行特征提取和降维，可以应用于数据挖掘，机器学习，人脸识别上！-Application of PCA for feature extraction and dimensionality reduction can be applied to data mining, machine learning, face recognition on!
machinelearning
- 机器学习 curse of dimensionality-Machine learning curse of dimensionality
gfoidl.SammonProjection_Source
- c#实现的基于非线性降维方法的数据分析程序代码-Sammon s projection is a nonlinear projection method to map a high dimensional space onto a space of lower dimensionality.
feisher
- PCA的步骤： 1 先将数据中心化； 2 求得的协方差矩阵； 3 求出协方差矩阵的特征值与特征向量； 4 将特征值与特征向量进行排序； 5 根据要降维的维数d’,求得要降维的投影方向； 6 求出降维后的数据； -PCA steps: 1 of the first data center 2 covariance matrix obtained 3 obtained covariance matrix ei
drtoolbox.tar
- 维数约简工具箱源程序及其代码MATLAB-Dimensionality reduction and its source code to MATLAB Toolbox
svm_wenxian
- 支持向量机是一种新颖的机器学习方法，主要用于模式识别、回归预测、函数逼近、参数估计。相比于其他的学习方法，支持向量机不仅克服了非线性，局部极小和维数灾难问题，而且具有更好的泛化能力。-Support vector machine is a novel machine learning method, mainly for pattern recognition, regression, function approximation, p
SubspaceLearningCodes(Matlab)forFaceRecognition.ra
- 人脸识别的子空间方法，包括LLE，ISOMAP和NPE等维数约减算法-Subspace method for face recognition, including LLE, ISOMAP and NPE dimensionality reduction algorithm such as
MATLABCodesforDimensionalityReduction
- 维数约减matlab工具箱，包括LLE，ISOMAP，NPE等，具有较好的效果-Dimensionality reduction matlab toolbox, including LLE, ISOMAP, NPE, etc., with good results
vstock61
- 离散小波变换，然后主成分分析进行数据降维，用于模式识别，如人脸识别，掌纹，-Discrete wavelet transform, and then principal component analysis for data dimensionality reduction for pattern recognition, such as face recognition, palm prints,
PCA
- 自己写的PCA降维算法，还有模糊k均值大家可以参考一下-Write their own PCA dimensionality reduction algorithm, and fuzzy k means we can refer to
laplacian_eigen
- Laplacian Eigenmaps [10] uses spectral techniques to perform dimensionality reduction. This technique relies on the basic assumption that the data lies in a low dimensional manifold in a high dimensional space.[11] This
progarmlab4
- The Principal component analysis, is a standard technique used for data reduction in statistical pattern recognition and signal processing A common problem in statistical pattern recognition is feature selection or fea
PCAaICA
- 主成分分析和独立成分分析,分别处理降维问题和盲信号分离问题-Principal component analysis and independent component analysis, dimensionality reduction, respectively, deal with the problems and blind signal separation
PCATry
- 人脸识别过程中的PCA降维例程，读者可借助理论分析例程，基于OpenCV2.0版本开源库 版，在VS2005 调试执行成功。包含400张人脸库-PCA face recognition in the process of dimensionality reduction routine, the reader can make use of theoretical analysis routines, based on open-sou
Dimension-reduction--toolbox
- 该工具箱中包含了多种降维算法。其中有传统的PCA和Local PCA算法，也有典型的流形学习算法，如Isomap、LLE、HLLE、Laplacian Eigenmaps 和 Local Tangent Space 。-The toolbox contains a variety of dimensionality reduction algorithms. In which the traditional PCA and Local
1127647code_tar
- matlab code for Science2006 reduce dimensionality with nueral network-code for Science2006 reduce dimensionality with nueral network
swissroll
- 基于LLE（局部线性嵌入）算法的瑞士卷降维程序，程序自动生成瑞士卷，然后降维输出图像。-Based on LLE (locally linear embedding) dimensionality reduction algorithm Swiss roll program, the program automatically generates Swiss roll, then drop-dimensional output imag
Isomap
- Isomap流形降维算法，包括了一个瑞士卷生成数据，dijk距离算法。-Dimensionality reduction algorithm Isomap manifold, including the formation of a Swiss roll data, dijk distance algorithm.
pca-deductional-vector
- pca降维 在pca提取vd后可以利用降维进行更加简便的操作-pca pca extraction vd dimension reduction in the dimensionality reduction can be used after a more simple operation