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Description: 线性判别方法，人脸数据库上的LDA程序，基于Matlab，供学习使用-Linear discriminant method, human face database of LDA procedures, based on Matlab, for learning to use
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Author: 吴梦 |
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Description: 非线性降维方法 可以应用于高维数据的机器学习-Nonlinear dimensionality reduction methods can be applied to high-dimensional data, machine learning
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Author: 王博 |
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Description: 《机器学习》课上的作业，PCA和LDA降维，尽管网上很多，但很少注释，另外细节上也没注意。这里有很详细的注释。另外还附上一个Naive贝叶斯分类器，大家可以作比较。附带的图像包是OLR人脸。ReducedDim为想要提取的特征数，不是百分比！-" Machine learning" classes on the homework, PCA and LDA dimensionality reduction, even though a lot of online, but few notes, on the other did not pay attention to details. Here there is a very detailed notes. In addition, attach a Naive Bayesian classifier, we can compare. Fringe image packages are OLR people face. ReducedDim you want to extract the characteristics of a few, not a percentage!
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Description: 2DPCA用于人脸、步态等图像识别，可先按照行列比例将不规整图像归一化处理，然后进行训练，并且识别，全部中文注释和提示，便于学习和参考。-2DPCA human face, gait, such as image recognition, in accordance with the ranks of the ratio can not structured to deal with the normalized image, and then training, and recognition, all Chinese notes and tips for learning and reference.
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Size: 3072 |
Author: 张天源 |
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Description: 线性判别分析（LDA）用于特征选择，可以对数据集或者图像提取有用特征，用于分类或者聚类等机器学习应用中-Linear Discriminant Analysis (LDA) for feature selection, application in dataset or image feature extraction, for classification or clustering applications in machine learning
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Author: 苗晨 |
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Description: 子空间学习的代码，主要包括人脸识别中常用的特征提取算法如pca lda 以及目前常见的流行学习的相关代码-Subspace learning the code, mainly including commonly used in face recognition feature extraction algorithms such as pca lda and the current prevalence of common learning-related code
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Size: 173056 |
Author: dd |
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Description: Machine Learning Java Eclipse code which goes along with Stephen Marsland s book Machine Learning
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Author: c0ldlimit |
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Description: lda经典算法，c++编写，适合机器学习初学者使用-lda classical algorithm, c++ is written for beginners to use machine learning
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Size: 1579008 |
Author: zhucehao |
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Description: 文本分类模型LDA综述，机器学习贝叶斯网络模型-Text classification model LDA overview of machine learning Bayesian network model
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Size: 1145856 |
Author: 许亮 |
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Description: LDA的学习资料的合计！有MATLAB的实现例子！-Total LDA learning information! MATLAB examples of realization!
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Size: 371712 |
Author: 11 |
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Description: 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
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Size: 32768 |
Author: LYH |
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Description: LDA学习用到的算法，不是自己写，别人的，拿来学习用-LDA learning algorithm is used, not her own writing, others, used to learn
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Size: 1024 |
Author: 孙会文 |
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Description: lda的C++朴素实现，gibbs采样，学习lda必备-lda simple realization of C++, gibbs sampling, learning essential lda
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Size: 353280 |
Author: hal |
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Description: 是LDA的matlab例程，对初学者学习lda算法有帮助，能直接运行。-Is LDA matlab routines for beginners learning algorithms help lda can be run directly.
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Size: 5120 |
Author: 刘松 |
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Description: 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,新手学习的良好素材-Linear discriminant analysis (Linear Discriminant Analysis, LDA), also known as Fisher linear discriminant (Fisher Linear Discriminant, FLD), is a classic pattern recognition algorithms, a good novice learning material
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Size: 2048 |
Author: 伦格 |
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Description: 最强大的机器学习分类器之一，最好的贝叶斯分类器之一。-One of the most powerful machine learning classifier, one of the best Bayesian classifier.
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Author: jirongzi |
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Description: LDA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。文档到主题服从Dirichlet分布，主题到词服从多项式分布。
LDA是一种非监督机器学习技术，可以用来识别大规模文档集（document collection）或语料库（corpus）中潜藏的主题信息。它采用了词袋（bag of words）的方法，这种方法将每一篇文档视为一个词频向量，从而将文本信息转化为了易于建模的数字信息。但是词袋方法没有考虑词与词之间的顺序，这简化了问题的复杂性，同时也为模型的改进提供了契机。每一篇文档代表了一些主题所构成的一个概率分布，而每一个主题又代表了很多单词所构成的一个概率分布。
对于语料库中的每篇文档，LDA定义了如下生成过程（generative process）：
1. 对每一篇文档，从主题分布中抽取一个主题；
2. 从上述被抽到的主题所对应的单词分布中抽取一个单词；
3. 重复上述过程直至遍历文档中的每一个单词。-LDA is a document theme generation model, also known as a three-tier Bayesian probability model that contains the words, topics and document three-tier structure. Dirichlet distribution of the document to the theme of obedience, the theme to the word obey polynomial distribution.
LDA is an unsupervised machine learning techniques can be used to identify large-scale document set (document collection) or corpus (corpus) of the underlying themes of information. It uses the word bag (bag of words) of the method, which each one document as a word frequency vector, thus the text information into digital information for ease of modeling. However, the method does not consider the order of the words Bag between words, which simplifies the complexity of the problem, but also for the improvement of the model provided an opportunity. Each document represents a probability distribution of some of the topics posed, and each topic and they represent many words constituted a probability distribut
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Author: yangling |
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Description: 斯坦福大学公开课机器学习线性判别分析的笔记-Stanford open class machine learning linear discriminant analysis notes
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Size: 762880 |
Author: 张乐平 |
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Description: 用于中文文本的lda主题模型的代码，供学习主题模型的参考-A Chinese LDA topic model code for learning topic model reference
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Size: 62464 |
Author: 傅玮萍 |
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Description: LDA的一篇介绍。 LDA的全称是Linear Discriminant Analysis（线性判别分析），是一种supervised learning。LDA是在目前机器学习、数据挖掘领域经典且热门的一个算法(An introduction to LDA. LDA's full name is Linear Discriminant Analysis (Linear Discriminant Analysis), is a supervised learning. LDA is a classic and popular algorithm in the field of machine learning and data mining)
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Author: adcxs
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