搜索资源列表
Aempcaal
- EMPCA算法的函数代码，附带有训练测试数据集，用用于特征降维等方面。 ，经测试可直接使用。 -The function code of the EMPCA algorithm with the training set of test data, for feature dimensionality reduction and other aspects. Has been tested and can be used directly.
Face-recognition-method
- 基于PCA 和BP 神经网络的人脸识别方法是针对 PCA 方法中存在的高维数问题和它对未训 练过的样本识别率低的缺点而提出的。该方法在预处理的基础上，利用粗糙集对 PCA 降维处理后的人脸特征进行约简，提取其中分类能力强的特征，实现在识别精度不变的情况下，有效的去除冗余信息；然后将约简后的属性输入到神经网络进行规则提取，利用神经网络非线性映射和并行处理的特点，增强对人脸图像识别的泛化能力。实验证明，使用该方法在识别率上有一定的提高-Face recognition method based
2D-LDA
- LDA是一种线性降维方法，对原有的高维人脸数据集降维，然后识别，具有很好的聚类和识别效果。有详细的说明-LDA is a linear dimensionality reduction method, the original high-dimensional face data set dimensionality reduction, and then identify clustering and identification. Described in detail
pcaceshi
- 颜色特征HSV模型，用pca降维，已经测试成功-pca dimensionality reduction
PCA
- C++语言写的PCA降维算法，里面有两个主元分析C++代码-PCA language C++ dimensionality reduction algorithm, there are two principal component analysis C++ code
Hypercube
- 高光谱遥感影像数据降维处理 包括线性降维和非线性降维处理-dimension reduction
DarionALToolbox
- 高光谱遥感影像数据降维处理 包括线性降维和非线性降维处理-Hyperspectral remote sensing image data to reduce the dimension of linear dimensionality reduction and nonlinear dimensionality reduction processing
jiangwei
- 在科学研究中，我们经常遇到对大量高维数据进行处理的问题，本文是对数据降维算法的简要总结。-In scientific research, we often encounter the problem of handling a large number of high-dimensional data, the article is a brief summary of the data dimensionality reduction algorithm.
IsomapR1
- isomap代码是一种新的用于数据降维的方法，它在2000年被提出，发表在science杂志上。-isomap is a new dimensionality reduction method.
Jonathan-Huangpca-pca-jiang-wei
- 人脸特征提取LDA特征，Jonathan Huang大师编的降维。-Facial feature extraction LDA dimensionality reduction of features, master series.
ProjectPenalty
- 一种无损降维的方法论文，使用投影惩罚和核函数进行分类器的训练选择-A nondestructive method of dimensionality reduction papers, projection punishment and the kernel function classifier training options
FaceRec
- 人脸识别系统 PCA降维， SVM 分类， 40*10人脸数据库 对机器视觉 智能识别有帮助 -face recognition
REDUCTION-FOR-MIL--
- 为MIL,即multiple instance learning,多实例学习，来进行特征降维，大大减少计算量。2010年,IEEE收录的。-MIL, the multiple the instance learning and multi-instance learning for feature dimensionality reduction, greatly reduce the amount of calculation. In 2010, the IEEE included.
predata3pca
- 用PCA算法对中文文本数据进行降维，然后再将结果可视化显示-PCA algorithm to reduce the dimensionality of the Chinese text data, then the results of visual display
improved-FCM
- 用LLE算法对视频帧进行降维处理，然后用FCM算法对其进行视频摘要关键帧提取-LLE algorithm to reduce the dimension of the video frame data dimensionality reduction, and then use the FCM algorithm for key frame extraction
breast-cancer
- 用ISOMAP算法对癌症数据进行降维处理，然后再对降维后的数据进行可视化分析-ISOMAP algorithm to reduce the dimensionality of cancer data processing, data dimensionality reduction and then to visualization analysis
PCA
- 应用主成分分析的方法实现数据降维，主成分个数通过累积方差贡献率的方法来确定-The principal component analysis of data dimensionality reduction, the number of principal components to determine the cumulative variance contribution rate
lda_hash
- 以SIFT特征为目标输入，LDAHash方法进行降维实现目标识别-SIFT features input LDAHash method to reduce the dimensionality of the target recognition
sift_LDA
- 利用LDA对目标SIFT特征进行降维，实现目标分类-LDA to reduce the dimensionality of the target SIFT features to achieve the target classification
DRTOOL_drtoolbox
- matlab 降维工具箱，最新版本。包含各类线性及非线性降维代码，lle,lpp,mvu,isomap,npe等皆在其中。-DRTOOL, by itself, creates a new DRTOOL or raises the existing singleton*. H = DRTOOL returns the handle to a new DRTOOL or the handle to the existing single