Description: Parzen窗函数概率密度估计演示程序
完全按照《现代模式识别》孙即祥著作 2.4.4《动态聚类法》算法3实现
使用欧式距离作为测度标准。-Parzen window probability density function is estimated demo program in full accordance with the Platform: |
Size: 1024 |
Author:潘水洋 |
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Description: 这是一个模式识别中的parzen窗的一个简单仿真分类实例，其中female.txt和male.txt是训练样本，test.txt是测试样本，分类效果非常好，对于模式学习的初学者将会有很大帮助。-This is a pattern recognition in a simple window parzen Category simulation examples, one of female.txt and male.txt training samples, test.txt is the measurement, classification effect is very good for beginners will be learning model has very big help. Platform: |
Size: 2048 |
Author:刘锐 |
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Description: 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 the decision rules to identify with the ability of automatic classification. This paper introduces the Parzen window method using a random pattern classifier, and achieved a simple matlab random pattern classifier. Platform: |
Size: 287744 |
Author:丑力 |
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Description: 本实验的目的是学习Parzen窗估计和k最近邻估计方法。在之前的模式识别研究中，我们假设概率密度函数的参数形式已知，即判别函数J(.)的参数是已知的。本节使用非参数化的方法来处理任意形式的概率分布而不必事先考虑概率密度的参数形式。在模式识别中有躲在令人感兴趣的非参数化方法，Parzen窗估计和k最近邻估计就是两种经典的估计法。(The purpose of this experiment is to study the Parzen window estimation and the k nearest neighbor estimation method. In previous pattern recognition studies, we assume that the parameter form of the probability density function is known, that is, the parameter of the discriminant function J (...) is known. This section uses nonparametric methods to handle any form of probability distribution without having to consider the parameter form of probability density. In pattern recognition, there are hidden nonparametric methods that are interesting. Parzen window estimation and K nearest neighbor estimation are two classical estimation methods.) Platform: |
Size: 2048 |
Author:bss
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Search - parzen window in matlab