搜索资源列表
lda
- 一个基于人耳模式识别的lda算法,可实现对高维矩阵的降维。-A pattern recognition based on human ear lda algorithm can realize high-dimensional matrix of dimension reduction.
LDA
- LDA MATLAB的算法,可以加入iris数据,并且直接可以使用的-LDA MATLAB algorithm, can join the iris data, and can be used directly
LDA
- 一个LDA的算法,可以实现对实现基于LDA的人脸识别-An LDA algorithm, can achieve the realization of Face Recognition Based on LDA
lda
- This code is LDA base face recognition programme. It reads nots faces from ORL database a
LDA
- 关于LDA算法在人脸识别应用中的研讨及比较-About LDA application on face detec
2D-LDA
- 2D-LDA, used for classification.
2D-LDA
- 2d-lda的一些matlab算法,此法效率较高,值得学习学习哈-2d-lda some matlab algorithm, this method is more efficient, should learn from Kazakhstan
pca-lda
- face recognitionand detection by lda,pca
LDA-face-recognition
- 使用基于LDA算法的人脸识别程序(附有相应的论文)-LDA based face recognition program(papers included)
lda-c-dist
- 在linux下的LDA算法, 用于数据挖掘,可直接编译运行。-In linux the LDA algorithm for data mining, can be directly run the compiler.
LDA
- 有几类样本点,试利用LDA分类器、求出其分界面,并分析这类分类器的特点。-There are several types of sample points, try using Fisher classifier, find the sub-interface, and analyze the characteristics of such classification.
Labeled-LDA-model-text-classify
- 基于Labeled-LDA模型的文本分类新算法-Labeled-LDA model based on the new algorithm for text categorization
LDA
- LDA for face recognation matlab code
LDA
- LDA matlab code 线性判别式分析(Linear Discriminant Analysis, LDA),也叫做Fisher 线性判别 (Fisher Linear Discriminant ,FLD),是模式识别的经典算法,它是在1996 年由Belhumeur 引入模式识别和人工智能领域的。性鉴别分析的基本思想是将高维的模式样本投影到最佳鉴 别矢量空间,以达到抽取分类信息和压缩特征空间维数的效果,投影后保证模式样本在新的 子空间有最大的类间距离和最小的类内距离,即模式在该空间中有
用PCA(非工具包,自写)实现LDA
- 上了一门统计分析的课程,所有课程所学内容均不允许使用工具包,特自写PCA,实现LDA线性分类,希望可以与大家分享,一起学习参考,
gait recognition with DTW PCA LDA
- code for gait recognition with DTW PCA LDA matlab
LDA算法实现人脸识别
- 自己撰写的LDA算法实现简单的人脸识别,用ORL库来做测试。
LDA代码分析
- 对文本用LDA进行分类,LDA(Latent Dirichlet Allocation)是一种文档主题生成模型,也称为一个三层贝叶斯概率模型,包含词、主题和文档三层结构。(The text is classified with LDA)
BF-LDA
- 通过LDA模型抽取文档中得主题词汇,并通过背景和前景的比较生成最近更新的新生主题(Using LDA model to generate the topic word. By comparing the words generate from foreground and background, this model can analyze the newest topics.)
LDA
- Basic code for LDA understanding