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支持向量积的一些分类器训练的matlab代码-support vector plot of some classifier training Matlab code
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H-K(Ho-Kashyap)算法。在模式识别应用中运用HK算法根据样本进行分类器训练。,HK (Ho-Kashyap) algorithm. Applications in pattern recognition algorithm based on the use of HK classifier training samples.
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Fisher线性判别分类器源代码，包括训练函数和测试函数。-Fisher Linear Discrimination (FLD) classifier source code, including training function and test function.
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一个比较简单的模式识别问题。用female.txt 和male.txt 的数据作为训练样本集，建立Bayes 分类器，用测试样本数据set1.txt、set2.txt、set3.txt 对该分类器进行测试,分别应用单个特征及两个特征进行实验-A relatively simple pattern recognition problem. Female.txt and male.txt use data as a training sample set, the establishment of
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MATLAB编写的误差反向传播（BP）神经网络简单分类器。-MATLAB prepared by error back-propagation [BP] neural network classifier easy.
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采用身高和体重数据作为特征，分别假设二者相关或不相关，在正态分布假设下估计概率密度，建立最小错误率Bayes分类器，写出得到的决策规则，将该分类器应用到训练/测试样本，考察训练/测试错误情况。-The use of height and weight data as the characteristics of the assumption that the two were related or not related to the normal distribution probabilit
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（压缩包里一共有5个代码）
pca+lda+粗糙集+模糊神经网络
saveORLimage.m将ORL人脸库分为测试集ptest和训练集pstudy存为imagedata.mat
1.savelda.m将人脸库先进行pca降维，再用lda进行特征提取，得到新的测试集ldatest和训练集ldastudy存为imageldadata.mat
2.对ldastudy进行离散化(discretimage.m)，得到离散化矩阵disdata,存入到imagedisdata.mat
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分类器的训练与学习是模式识别的一个重要环节,其目的在于按照某种算法,确定判决规则,使之具有自动分类识别的能力。本文介绍了采用Parzen窗法的随机模式分类器,并matlab实现了一个简易的随机模式分类器。-Classifier training and learning is an important part of pattern recognition, in accordance with the purpose of some kind of algorithm to determine
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Construct a linear SVM classifier from the training Samples and Labels
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通过用最小距离分类判别方法，用MATLAB程序找出最小距离分类判别时的识别界面，从而进行识别已知的两类训练样本，并分析其识别错误率。-By using minimum distance classifier discriminant method, using MATLAB program to find the minimum distance classifier recognition interface when the judge, which is known to identify
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图象处理 模式识别 多种分类方法(最临近匹配分类器、Bayes分类器、线性函数分类、非线性函数分类、神经网络分类)识别0-9数字 手写数字与数字图片,包括设计训练样品库、可以选择多种分类器来识别识别0-9这十个阿拉伯数字，包括临时手写的数字，也包括图片中的数字
-Pattern recognition image processing a variety of classification (the most close to matching classifier, Bay
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adaboost源码Adaboost是一种迭代算法，其核心思想是针对同一个训练集训练不同的分类器(弱分类器)，然后把这些弱分类器集合起来，构成一个更强的最终分类器(强分类器)。-adaboost source is an iterative algorithm Adaboost, the core idea is that a training set for the same training the different classifiers (weak classifier), then
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用fisher分类器实现简单的分类，首先进行样本的训练，然后对待测样本进行测试，程序中画出了分界面。-Fisher classifier with a simple classification, first of all to the training sample, then treatment of test samples for testing, the interface of the program are drawn.
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贝叶斯分类器的分类原理是通过某对象的先验概率，本文详细介绍贝叶斯分类器，使用贝叶斯分类器对样本进行训练分类，得到良好分类结果，并对分类结果进行分析。-Principle of Bayesian classifiers is through prior probability of an object, the paper describes Bayesian classifier, Bayesian classifier using the training sample classificat
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This is the source code for a Single Vector Machine classifier, briefly called a SVM classifier.
There are 60 peices assigned for training and 30 for testing the classifier.
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matlab图像特征识别。分类器的训练方法。很好的学习资料。如何用OpenCV训练自己的分类器。内含人脸库共训练器使用-matlab image feature recognition. Classifier training methods. Good learning materials. How to use OpenCV train their own classification. Training face database containing a total of uses
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The early detection of arrhythmia is very important
for the cardiac patients. This done by analyzing the
electrocardiogram (ECG) signals and extracting some features
from them. These features can be used in the classification of
different typ
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经典的Adaboost分类器训练过程详细的matlab代码解释，对做模式识别的人很有用-Classic Adaboost classifier training process explained in detail matlab code, to do pattern recognition is useful
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人脸检测中弱分类器的训练，是matlab程序，通过正负样本图片，可得出弱分类器-Face detection in the weak classifier training is matlab program, through positive and negative sample picture can be drawn from the weak classifier
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使用pca方法对图像进行特征提取，对训练集的20个人的共一百张人脸进行训练，使用adaboost算法生成强分类器，可以对测试集的人脸图片进行识别，且识别率较高(The PCA method is used to extract the features of the image, and the training is carried out for a total of 100 faces of 20 people in the training set. The AdaBoost algor
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