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matlab K近邻分类法
- matlabK近邻法实现
K-近邻法
- 用于模式识别
Parzen_KNN
- Parzen 窗 和 K近邻法进行概率密度估计 还带一个示波器控件.-Parzen window and K-nearest neighbor method probability density is estimated to bring an oscilloscope control.
最近邻法分类器演示
- 本程序是一个最近邻分类算法的演示程序，本程序完成了三种最近邻的演示并实现算法的分析-this procedure is a nearest neighbor classification algorithm the demo program, the completion of a three- Nearest Neighbor algorithm demonstration and analysis
Classify_Homework
- 模式识别作业——用平均样本法，平均距离法，最近邻法和K近邻法进行分类-pattern recognition operations-- with the average sample, the average distance, nearest neighbor and K-nearest-neighbor classification
knn_demo
- K近邻法的matlab程序，发现大家都在找它！-K-nearest neighbor method of Matlab procedures, I found that we all have to find it!
Homework_191007
- 平台：VS2005 描述：这是华东师大模式识别课程的第三个Homework。用C#实现的人脸识别小程序，算法采用K阶近邻法，人脸图片来自Yale Database。上传的压缩文件里面有我的report和工程文件夹的打包。-Platform: VS2005 Descr iption: This is a pattern recognition course ECNU third Homework. With C# Applet to
knn
- 朴素贝叶斯(Naive Bayes, NB)算法是机器学习领域中常用的一种基于概率的分类算法，非常简单有效。k近邻法(k-Nearest Neighbor, kNN)[30,31]又称为基于实例(Example-based, Instance-bases)的算法，其基本思想相当直观：Rocchio法来源于信息检索系统，后来最早由Hull在1994年应用于分类[74]，从那以后，Rocchio方法就在文本分类中广泛应用起来。-Naive
PatternRecognition
- 1.Fisher分类算法 2.感知器算法 3.最小二乘算法 4.快速近邻算法 5.K-近邻法 6.剪辑近邻法和压缩近邻法 7.二叉决策树算法-1.Fisher Classification Algorithm 2. Perceptron algorithm 3. Least-squares algorithm 4. Fast nearest neighbor 5.K-neighbor method 6. Clip
knn
- knn k近邻算法，可选择欧式距离或者曼哈顿距离-knn k nearest neighbor, Euclidean distance or Manhattan can choose the distance
KNearestCls
- 模式识别中的K近邻法和快速K近邻法的VC＋＋实现-Pattern Recognition and rapid K neighbors K neighbors law VC to achieve
KwithC-neighbor
- 用C语言对K近邻法进行的模式识别，包括说明及程序。-K with C-neighbor method of pattern recognition, including a descr iption of and procedures.
linjin
- 用k近邻法和剪辑近邻法分类样本点，模式识别实验内容之一-K neighbors with neighbors and editing sample points classification, pattern recognition one experiment
2rar
- 用matlab写的最近邻和K近邻法分类器，简单易懂，适合初学者-Written with matlab and K-NN nearest neighbor classifier, easy to understand for beginners
ClassifyHomework
- 模式识别,用平均样本法、平均距离法、最近邻法、K近邻法进行分类。-Pattern recognition, with an average of the sample method, the average distance method, nearest neighbor, K-NN classification.
knn
- knn-K近邻法实现两分类的函数代码，输入为两类的样本特征，和待测试的样本向量，输出为分类结果。-knn-K nearest neighbor method to achieve the two categories of function code, enter the characteristics of two types of samples, and samples to be tested vector, the outpu
zuijinlinfenlei
- 我们使用MATLAB软件实现了人脸识别并统计其识别率。本实验采用PCA（主成分分析）方法，利用K-L变换和奇异值分解原理实现。并分别采用最近邻法分类器得出它们的成功率。-We use face recognition software and the MATLAB Statistics recognition rate. The present study, PCA (principal component analysis) meth
K
- K近邻法对Iris数据分类，输入分类结果和准确率。-K-nearest neighbor method for Iris data classification, enter the classification results and accuracy.
KNN_demon
- 最近邻法语k近邻法的例子，基于matlab平台，有助于初学者学习。(The recent example of the nearest neighbour approach to French K, based on the MATLAB platform, helps beginners to learn.)
k-近邻点估计点云法向量
- 利用matlab实现k-近邻点估计点云法向量求解，(Matlab is used to solve the normal vector of k-nearest neighbor point cloud.)