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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 PCA algorithms, there are the
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普通降维方法汇总，PCA，LDA,isomap-Summary of general dimension reduction methods, PCA, LDA, isomap .......
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This toolbox is an educational and recreative toolbox around recent ideas in the field of dimension reduction.
* PCA : classical Principal Componnent Analysis (linear projection).
* Nonlinear dimensionality reduction by locally linear embedding
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Paper implementation of
Adaptive Dimension Reduction Using Discriminant Analysis and K-means Clustering
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adaptive dimension reduction for clustering high dimensional data
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标准LSI方法，广泛用于降维等模式识别问题-Standard LSI method, widely used for dimension reduction such as pattern recognition problem
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快速PCA计算方法，有效实现降维等操作，和特征选择-Fast PCA method of calculation of effective dimension reduction and other operations, and feature selection
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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.
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MATLAB源程序，主成分分析法（PCA），这是一种降维的方法，可以用于多通道数字信号处理-MATLAB source code, principal component analysis (PCA), which is a dimension reduction method can be used for multi-channel digital signal processing
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PCA技术的一大好处是对数据进行降维的处理。我们可以对新求出的“主元”向量的重要性进行排序，根据需要取前面最重要的部分，将后面的维数省去，可以达到降维从而简化模型或是对数据进行压缩的效果。同时最大程度的保持了原有数据的信息。-A major advantage of PCA technology is reduce the dimension of the data processing. We can calculate the new " principal component&qu
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PCA+LDA人脸识别，识别率高于单独PCA或LDA算法。需要matlab dimension reducation toolbox。-Face verification using PCA and LDA fusion. Better performance than single PCA or LDA algorithm. The image database is included. Matlab dimension reduction toolbox is requrired.
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光谱空间的主成分分析 PCA ：旨在利用降维的思想，把多指标转化为少数几个综合标。-Principal component analysis of spectral space PCA: dimension reduction ideas to use to index into a few more comprehensive standard.
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pca特征向量提取 利用pca的方法获取特征植及特征向量 最后可以自己根据需要降维-pca pca feature vector extraction method using characteristics of plants and to obtain the final feature vector dimension reduction can be their own as needed
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一个关于数据降维的工具包，外国牛人编写，囊括了各种降维方法，是一个很好的工具！-A tool for data reduction package, foreign cattle were written, include a variety of dimension reduction method is a good tool!
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关键词:文本分类 特征降维 规则抽取 模式聚合 粗糙集
-Keywords: text classification feature dimension reduction rule extraction model aggregation rough set
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OpenCV中PCA实现人脸降维，基于QT实现-OpenCV PCA face dimension reduction
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多种降维算法,包括lle,lpp,ltsa-many kinds of dimension reduction method
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pca lda kpca klda lpp matlab 特征降为方法，对于新手比较有用。-pca lda kpca klda lpp matlab code for dimension reduction. these are very useful for new researchers.
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降维算法，在遇到维数比较高的时候，用该算法-Dimension reduction
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使用降维积分方法，计算结构的静态可靠度。将功能函数的维度降低，而后进行高效的积分。(Dimension Reduction Integration methods for structural reliability.)
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