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Description: 用EM算法估计PCA参数，效果比传统的PCA要好，原文发表于神经计算杂志上，有兴趣者可以先看论文。-using EM algorithm parameters estimated PCA results than the traditional PCA better, in the language of neural computation published in the magazine, those who are interested can read papers.
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Author: 武旗 |
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Description: 用EM算法估计PCA参数，效果比传统的PCA要好，原文发表于神经计算杂志上，有兴趣者可以先看论文。-using EM algorithm parameters estimated PCA results than the traditional PCA better, in the language of neural computation published in the magazine, those who are interested can read papers.
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Size: 159744 |
Author: 武旗 |
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Description: PPCA变换的MATLAB程序代码 需要的可以下载
-PPCA transform MATLAB program code needed to download
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Size: 430080 |
Author: yuefeng |
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Description: 关于EM的详细讲解,条理清楚,易于理解,方便初学者使用-Detailed briefings on the EM, coherent, easy-to-understand, easy for beginners to use
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Size: 188416 |
Author: 塞北 |
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Description: 统计模式识别算法包，包括线性分类算法，SVM，PCA，LDA，EM，k-means分类等多种常用的模式识别算法。-Statistical pattern recognition algorithm package, including a linear classification algorithm, SVM, PCA, LDA, EM, k-means classification and many other commonly used pattern recognition algorithms.
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Size: 5998592 |
Author: Xiaoyue Jiang |
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Description: I present an expectation-maximization (EM) algorithm for principal
component analysis (PCA).
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Size: 121856 |
Author: sreenath |
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Description: An implemantation of PCA by EM algorithm
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Size: 159744 |
Author: kathie |
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Description: Probabilistic Principal Component Analysis
– Latent variable models
– Probabilistic PCA
• Formulation of PCA model
• Maximum likelihood estimation
– Closed form solution
– EM algorithm
» EM Algorithms for regular PCA
» Sensible PCA (E-M algorithm for probabilistic PCA)
– Mixtures of Probabilistic Principal Component
Analysers-Probabilistic Principal Component Analysis
– Latent variable models
– Probabilistic PCA
• Formulation of PCA model
• Maximum likelihood estimation
– Closed form solution
– EM algorithm
» EM Algorithms for regular PCA
» Sensible PCA (E-M algorithm for probabilistic PCA)
– Mixtures of Probabilistic Principal Component
Analysers
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Size: 263168 |
Author: Tatyana |
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Description: finds the first k principal components of a dataset and their associated eigenvales using the EM-PCA algorithm
-finds the first k principal components of a dataset and their associated eigenvales using the EM-PCA algorithm
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Size: 4096 |
Author: sala |
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Description: 模式识别工具箱函数，包含多种模式识别方法如KNN，PCA，SVM,C4.5,EM算法-Pattern recognition toolbox functions, including a variety of pattern recognition methods such as KNN, PCA, SVM, C4.5, EM algorithm, etc.
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Size: 362496 |
Author: Arthur |
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Description: stprtool的使用文档，非常好的模式识别工具包，里面有关于核的以及贝叶斯的相关程序，以及PCA，EM，SVM等方法。 -stprtool the use of the document, very good pattern recognition tool kit, which has nuclear as well as Bayes procedures, as well as PCA, EM, SVM and other methods.
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Size: 923648 |
Author: wangpw |
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Description: 数据挖掘：KDD 过程，不同类型数据的距离度量方式，小波 PCA 属性子集选择-KMean KModoid BIRCH CHEMELEON
DBSCAN OPTICE STING CLIQUE EM SCAN
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Size: 26707968 |
Author: fangqingwu |
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Description: Max Welling s Notes 原网页是PS格式的，我都转成了pdf格式方便阅读，机器学习算法相关，都是一些相对基础的算法，这个笔记把很多算法的精髓都整理的很清楚，适合初学者入门看，以及一些新的算法里面可能没有涉及，在英文描述中我把里面涉及的算法列了一下，按需求下载吧。-Max Welling s Notes。Statistical Estimation [ps]
- bayesian estimation
- maximum a posteriori (MAP) estimation
- maximum likelihood (ML) estimation
- Bias/Variance tradeoff & minimum description length (MDL)
Expectation Maximization (EM) Algorithm [ps]
- detailed derivation plus some examples
Supervised Learning (Function Approximation) [ps]
- mixture of experts (MoE)
- cluster weighted modeling (CWM)
Clustering [ps]
- mixture of gaussians (MoG)
- vector quantization (VQ) with k-means.
Linear Models [ps]
- factor analysis (FA)
- probabilistic principal component analysis (PPCA)
- principal component analysis (PCA)
Independent Component Analysis (ICA) [ps]
- noiseless ICA
- noisy ICA
- variational ICA
Mixture of Factor Analysers (MoFA) [ps]
- derivation of learning algorithm
Hidden Markov Models (HMM) [ps]
- viterbi decoding algorithm
- Baum-Welch learning algorithm
Kalman Filters (KF) [ps]
- kalman filter algorithm (very detailed derivation)
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Author: 陈希 |
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Description: 在这个项目中，我们的目标是建立一个识别和大小231x231图像呈现对象分类系统。我们得到了一组训练图像，每四个标签之一：1飞机；汽车2；3马，否则。我们提供了两个特点：一是方向梯度直方图（HOG），其尺寸为5408；另一个是overfeat ImageNet美国有线电视新闻网的特点，其尺寸37000。关于测试图像，我们只给出了每个图像的功能，没有标签，结果判断由平地机。我们的目标是提供二进制和多个预测。平衡错误率（BER）是我们的性能评估。为了解决这个问题，我们首先减少PCA的问题的维数，处理不平衡数据集，通过向上采样或下采样，去除异常值，通过无监督学习，如k-均值和EM算法。其次，我们使用ML方法，如二进制和多项式logistic回归，二进制和多项式SVM和神经网络。多项式SVM的证明有最好的结果。最后，我们在100分中得了92分。-In this project, our goal was to build a system that recognizes and classifies the object present in an image of size 231x231. We were given a set of training images each with one of four labels: 1 for airplanes 2 for cars 3 for horses 4 otherwise. We were provided with two sets of features: one is Histogram of Oriented Gradients (HOG), which has dimension of 5408 the other one is OverFEAT ImageNet CNN Features, which has dimension of 37,000. Concerning the test images, we were only given the features of each image without label, and the results to be judged by the grader. Our goal was to provide binary and multiple predictions. The Balanced Error Rate (BER) was our performance uator. To solve the problem, we firstly reduced the problem’s dimensionality by PCA, dealt with imbalanced datasets through up-sampling or down-sampling, and removed outliers through unsupervised learning such as K-Means and EM Algorithm. Secondly, we applied ML methods such as Binary and Multinomial Logist
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Author: 杨雪 |
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Description: 创建你的第一个贝叶斯网络 手工创建一个模型 从一个文件加载一个模型 使用 GUI 创建一个模型 推断 处理边缘分布 处理联合分布 虚拟证据 最或然率解释 条件概率分布 列表（多项式）节点 Noisy-or 节点 其它（噪音）确定性节点 Softmax（多项式 分对数）节点 神经网络节点 根节点 高斯节点 广义线性模型节点 分类 / 回归树节点 其它连续分布 CPD 类型摘要 模型举例 高斯混合模型 PCA、ICA等 专家系统的混合 专家系统的分等级混合 QMR 条件高斯模型 其它混合模型 参数学习 从一个文件里加载数据 从完整的数据中进行最大似然参数估计 先验参数 从完整的数据中（连续）更新贝叶斯参数 数据缺失情况下的最大似然参数估计（EM 算法） 参数类型 结构学习 穷举搜索 K2 算法 爬山算法 MCMC 主动学习 结构上的 EM 算法 肉眼观察学习好的图形结构 基于约束的方法 推断函数 联合树 消元法 全局推断方法 快速打分 置信传播 采样（蒙特卡洛法） 推断函数摘要 影响图 / 制定决策 DBNs、HMMs、Kalman 滤波器等等(http://www.cs.ubc.ca/~murphyk/Software/BNT/bnt.html
http://www.cs.ubc.ca/~murphyk/Software/BNT/FullBNT-1.0.4.zip
http://hi.baidu.com/zgyz/blog/item/2d3627f415c7fbe77709d763.html
http://www.cs.ubc.ca/~murphyk/Software/BNT/bnt.html
http://www.ee.ic.ac.uk/hp/staff/dmb/voicebox/voicebox.html)
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Author: qq1279
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Description: GMM高斯混合模型EM算法聚类，PCA主成分分析，以及从人脸图像中提取主成分(GMM Gauss hybrid model EM algorithm clustering, PCA principal component analysis, and extraction of principal components from face images)
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Author: linann
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