搜索资源列表
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脱机手写体识别Matlab源程序
包括特征提取、bayes分类器、K近邻分类及最近邻分类。
Testscr iptRecognition.m：测试代码
scr iptFeaExtract.m ：特征提取
KNearestEstimate.m ：K近邻估计
NearestEstimate.m : 最近邻估计
BayesTrain.m ：训练bayes分类器
Bayes.m ：测试bayes分类器
CrossValidate.m ：m交叉验证
-Offlin
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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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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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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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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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adboost分类器 matlab源程序 用于训练样本 实现分类-Adaboost classifier Matlab source for training samples to achieve classification
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在MATLAB中利用贝叶斯分类器对训练数据进行分类，然后利用测试数据对贝叶斯分类器的效果进行测试-The training data are classified using the Bayesian classifier in MATLAB, then use the data to test the effect of Bayesian classifier test
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svm分类器，训练svm的MATLAB代码，简单易理解，好用，能够有效的实现动能(SVM classifier, training SVM MATLAB code, simple and easy to understand, good use, can effectively implement the kinetic energy)
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概率神经网络(Probabilistic Neural Network)是由D.F.Speeht博士在1989年首先提出，是径向基网络的一个分支，属于前馈网络的一种。它具有如下优点：学习过程简单、训练速度快；分类更准确，容错性好等。从本质上说，它属于一种有监督的网络分类器，基于贝叶斯最小风险准则。(The rate neural network, first proposed in 1989, is a branch of the RBF network and is one of the fe
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一、用python或matlab编写一个KNN分类器
训练集为semeion_train.csv（手写体识别）
测试集为semeion_test.csv
计算在测试集上错误率（k=1,k=3,k=5,k=10）
?(1. Write a KNN classifier with Python or matlab
Training set is semeion_train.csv (handwriting recognition)
The test set is semeion_test
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