搜索资源列表
lda
- 模式识别的fisher线性判别分析lda方法-Pattern Recognition fisher linear discriminant analysis lda method
PCA-and-LDA-draw
- PCA和LDA的研究,我写了很久才做出来的，希望对大家有用，尤其是用在毕业设计上-A very useful tool to analysis PCA and LDA
LDA
- 线性判别分析LDA人脸识别代码，识别率计算-Linear discriminant analysis LDA face recognition code recognition rate
lda
- using functions for LDA
LDA-PCA-TLDA
- LDA\PCA\TLDA算法代码，内含orl人脸库-LDA \ PCA \ TLDA algorithm code, containing orl face database
LDA
- LDA是一种特征分类方法，这种方法是一种线性的方法。-LDA is a feature classification method, which is a linear method.
LDA
- 一款简单的人脸识别软件，里面包含四种算法。PCA LDA、零空间法、DLDA算法。不包括人脸库，因此需要自行下载人脸库！-A simple face recognition software, which contains four algorithms. PCA LDA, zero space law, DLDA algorithm. Does not include face database, so need to download face database!
lda
- it is matlab code for lda-it is is matlab code for lda
call-lda
- it is calll for lots of data set for lda
LDA
- LDA算法在matlab中的实例程序代码以及算法原理的讲解-LDA algorithm in matlab example code and algorithm explain
lda.cpp
- lda算法事例,vc++6.0实现，简单易懂，适合新手-LDA algorithm stories of
lda
- 基于lda的主题提取，从txt类型的源码中提取出整篇文档的关键字（主题）-lda model extraction
lda-c-dist
- lda贝叶斯文本分类器，c语言实现 linux运行环境-lda Bayesian text classifier, c language runtime environment linux
LDA
- LDA:线性判别分析方法。用于实现线性数据降维。采用K近邻分类器对数据进行分类-LDA: linear discriminant analysis method. Used to achieve linear data dimensionality reduction. Using K-nearest neighbor classifier for data classification
lda-java-src
- lda主题模型代码，希望对文档主题分析感兴趣的人有所帮助-lda topic model code
LDA-PCA-classifier
- this program will help you to perform LDA and PCA signal processing tools for classifing
LDA
- LDA算法（FLD）在matlab中的实现（含源代码和实现程序所需的随机数）-LDA algorithm (FLD) in matlab to achieve (including source code and procedures required to achieve a random number)
lda-c-dist
- Blei的LDA代码,隐式狄利克雷分配,实现了文档中主题的提取-LDA implementation, machine learning
a-direct-lda-algorithm
- Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference.
A-new-LDA-based-face
- Face recognition in a fuzzy method. Contains SVM, LDA, decision tree and so on, the effect is very good, worthy of reference.