搜索资源列表
贝叶斯和Fisher分类器的matlab源程序
- 基于Bayes和fisher的分类器,便于对通一批数据比较两个分类器的分类结果标有注视,简单易懂,用于初学者入门使用
贝叶斯分类器
- 贝叶斯一维分类器,用matlab编写,正态分布下男女生判别,最小错误率的贝叶斯分类
ExtractGLCM
- 灰度共生矩阵方法用来提供一幅图像的灰度共生矩阵值,然后送到分类器中进行分类-gray level co-occurrence matrix,a very important method of extracting features
adaboost.rar
- adboost分类器 matlab源程序 用于训练样本 实现分类 ,adboost classfication
fisher.rar
- 这是模式识别中线性分类器中最常用的fisher线性分类器,并在结果中画出了分类线和分类效果,This is image restoration in the Iterative Blind Deconvolution algorithm matlab source for the study of digital image has a lot of benefits!
Matlab贝叶斯分类器+(Bayers)程序
- 用matlab实现贝叶斯分类器,模式识别的一个程序。 matlab的英文教程
Bayes
- 使用matlab对基于最小错误率的Bayes分类器进行仿真,编写了相应的程序,分为协方差相等和不相等两种情况,最后画出了三类的分界线-Using matlab to the smallest error rate based on the Bayes classifier to carry out simulation, the preparation of the corresponding procedures, divided into equal covariance and unequ
Bayes_example
- Bayes分类器应用于IRIS数据集的例子-An example of Bayes Classifier applied on IRIS Data Set
Adaboost_train
- ADBOOST的训练代码,有供训练的数据,弱分类器训练,强分类器训练,和错误率,对理解ADABOOST是很好的例程-codes of adaboost traning,containing data for traning, implementation of weakleaner and cascad,and error as well,it can help us leaning ADABOOST
SVM-classifier
- 用matlab实现非线性支持向量机分类器对多类进行分类。-Using matlab to achieve non-linear support vector machine classifier for multi-class classification.
randomForest_4.5-36
- 随机森林分类器 可以实现分类 适合初学者学习参考-Neural network classifiers can be used to classify information for beginners to learn
PNN
- pnn分类器算法,用MATLAB源码,可以进行分类。-pnn classifier algorithm, using MATLAB source code can be classified.
libsvm-mat-2[1].89-3
- svm多分类器,包括多分类和GA算法和PSO算法优化的SVM-svm multi-classifier, including the multi-classification and GA algorithm and PSO algorithm for optimization of SVM
adaboost-Matlab
- 用matlab实现的adaboost分类器算法-Implemented with the matlab adaboost Classifier
matlab
- 模式识别中的线性分类器的设计,包括感知机,最小二乘法和支撑矢量机的算法的MATLAB代码。-Pattern Recognition linear classifier design, including perception, least squares and support vector machine algorithm MATLAB code.
非线性分类器设计
- 非线性分类器设计—支持向量机 matlab程序运行 非线性支持向量机(SVM)的原理、核函数类型 libSVM工具箱安装的一般流程(Nonlinear classifier design support vector machines)
各种分类器matlab程序
- 里面有随机森林,C4.5,ID3,SVM等分类器的matlab代码(There are random forest, C4.5, ID3, SVM classifiers matlab code)
线性分类器
- 该程序能够实现对于一个样本完成感知机,最小二乘法,凸优化方法解决SVM和matlab自带函数解决SVM的四种程序,并且通过修改部分参数可以完成不同效果。(The program can be achieved for a complete sample perceptron, least squares method, convex optimization method to solve SVM and MATLAB with four program function to solve th
KNN分类器
- 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
分类器
- 在matlab平台下,简单实现svm分类器功能(数据仓库与数据挖掘课程)(Simple implementation of SVM classifier)