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模式识别matlab工具箱,包括SVM,ICA,PCA,NN等等模式识别算法,很有参考价值-pattern recognition Matlab toolbox, including SVM, ICA, PCA, NN pattern recognition algorithms, and so on, of great reference value
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子模式主成分分析首先对原始图像分块，然后对相同位置的子图像分别建立子图像集，在每一个子图像集内使用PCA方法提取特征，建立子空间。对待识别图像，经相同分块后，分别将子图像向对应的子空间投影，提取特征。最后根据最近邻原则进行分类。-Sub-mode principal component analysis first of the original image block, and then the same sub-image, respectively, the location of the
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用mushrooms数据对模式识别课程讲述的各种模式分类方法[线性分类，Bayesian分类，Parzen窗，KNN]和特征选择和降维方法[PCA,LDA]进行了模拟，并给出了各类分类方法的结果，-It s the simulations about linear classification ,Bayesian ,Parzen and KNN of pattern recognition .And ,It gives the results.
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标准化后进行PCA特征提取，然后聚类分类-After standardized PCA feature extraction, clustering and classification
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基于PCA的图像分类的方法，该方法效果好，易理解。-PCA-based image classification method, the method effective, easy to understand.
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pca+ svm source code (matlab) matlab code, pca for feature extraction, svm classification
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In this code I have used GA in supervised PCA to find the best coeficients for overall covariance. the classification is made by K-In this code I have used GA in supervised PCA to find the best coeficients for overall covariance. the classification i
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This paper develops an efficient classification algorithm called UDP, which reduces the high dimension of sample to low dimensional subspace simply said as dimensionality reduction.UDP takes into account both the local and non-local quantities. It ca
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附件中包含各种各样的线性流形学习的降维算法（LPP，PCA，NPE。。。。），用于人脸识别，分类等等！-The annex contains a variety of linear manifold learning, dimensionality reduction algorithms (LPP, PCA, NPE....), For face recognition, classification, etc.!
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这是一个Matlab编写的基于PCA的人脸识别分类算法.-This is a Matlab prepared by the PCA face recognition classification algorithm.
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采用pca的方法，对样本进行分类。在实际中pca算法一般用于检测样本的相似度-Using pca method to classify the samples. In practice pca algorithm is generally used to detect the similarity of samples
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pcA,特征提取以及分类，可以运行.欢迎提意见，-pcA, feature extraction and classification, you can run
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自己写的MFA降维算法。此算法中先进行pCA处理原始数据，然后对处理后数据运用MFA，可用于人脸识别及其它分类问题。很好用。-Write your own MFA dimensionality reduction algorithm. This algorithm first performed pCA processing raw data, processed data and then use MFA, can be used for face recognition and other
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用于各种特征提取主成分分析法，如表情提取，人脸提取，识别分类等-For a variety of features to extract the principal component analysis (pca)，Such as expression extraction, face extraction, identification classification, etc
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此代码是采用PCA进行分类，神经网络进行自动识别，是自己手动编写的线性代码，有什么不对的地方，多多交流。-This code is the use of PCA classification, neural networks for automatic identification, is to manually write linear code, what is wrong with it, more exchanges.
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This the code for PCA (Principle component analysis). First PCA is used for dimension reduction. And then KNN is applied for classification.-This is the code for PCA (Principle component analysis). First PCA is used for dimension reduction. And then
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matlab工具箱,包括SVM,ICA,PCA,NN等等模式识别算法,很有参考价值--attern recognition Matlab toolbox, including SVM, ICA, PCA, NN pattern recognition algorithms, and so on, of great reference value
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用于主成分图像svm分类，简单，有很好的程序，适合初学者(SVM for principal component image classification, simple, there are very good procedures for beginners)
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A two-stage mechanism of ECG classification using Gaussian
mixture model(An automatic classifier for electrocardiogram (ECG) based cardiac abnormality detection using Gaussian mixture model (GMM) is presented here. In first stage, preprocessing tha
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对碰撞信号特征进行降维和聚类分析，提高分类精度(Reducing dimension and clustering analysis of collision signal features to improve classification accuracy)
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