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classification
- 该程序包实现了几个常用的模式识别分类器算法，包括K近邻分类器KNN、线性判别方程LDF分类器、二次判别方程QDF分类器、RDA规则判别分析分类器、MQDF改进二次判别方程分类器、SVM支持向量机分类器。 主程序中还有接口调用举例，压缩包中还有两个测试数据集文件。-The package to achieve a number of commonly used pattern recognition classifier algorithms, including K neighbor class
KNN_Classifier
- 仿真实现了KNN分类器的的一个功能，具有较好的分类效果。-Simulation of the KNN classifier of a function, with better classification results
KNNVB
- 最短距离法分类器VB实现，包括有详细例程说明-The shortest distance classifier VB to achieve, including a detailed descr iption routines
kNN_Matlab
- k-NN classifier in matlab
knn
- K-nearest neighbor classifier (k-NN) is a nonparametric approach for classification. It does not require the priori knowledge such as priori probabilities and the conditional probabilities. It operates directly towards the samples and is categorized
patternMiniPrj
- a code on pattern recognition which has pca as a dimentional reduction and knn as a classifier.
Classifier_min_Local_Mean_f
- 局部最小距离分类器，性能高于knn分类器，matlab环境下，可直接调用-Local minimum distance classifier, classifier performance than knn, matlab environment, can be called directly
neighborhoodclassifier
- 这是基于KNN的邻域分类器matlab代码，里面包含了KNN的matlab代码。-This is a neighborhood based on KNN classifier matlab code, which contains the KNN of matlab code.
KNNPandPneighborhoodPclassifier
- 模式识别knn分类器，matlab代码，k近邻算法-knn classifier ，matlab code
iss_l12
- pattern recognition ，knn classifier-pattern recognition ，knn classifier
knnclassifier
- Knn Classifier used for Various classification purposes
KNN-(2)
- 这个是基于matlab制作的KNN 识别器的写法-This is K-Nearest Neighbour classifier used in pattern recognition.
KNN-classifier
- 粗糙集的编码程序，包含多个模块，可供选择使用-Rough set of coding procedures, which includes multiple modules, choose to use
knnclassification
- 这是一个KNN分类器的matlab函数（K近邻分类器）,可自由选择参数k-it s a KNN classifier program of the matlab ,you can chose the parameter k to conduct the classify procedure
knn
- K近邻分类器，用于模式识别等领域，该程序短小精悍，适合与ANN和SVM进行比较研究，本人多篇论文用到，效果较好。-K-nearest neighbor classifier is often used in pattern recognition and other fields. It is suitful for a comparative study with ANN and SVM. I have published some papers used the code. The effe
wavelet-transform-using-knn
- 基于双低频小波变换和k近邻分类器的人脸识别算法源程序-Dual low frequency wavelet transform and k-nearest neighbor classifier based face recognition algorithm source
knn
- 本程序中,训练样本集含有30个样本,矢量长度为5,对样本{1,18,11,11,0.5513196}进行K=5的K-最近邻分类. 样本从文件data.txt中读取，程序运行结果显示所有样本以及其类别，待分类样本所属的类别（{1,18,11,11,0.5513196}属于"2"类），以及它的5个最近邻的类别和与它之间的距离。-In this program, the training sample set containing 30 samples, the vector length
knn
- matlab程序源代码，能够正确实现，最近邻分类-matlab program source code, to be able to correctly implement the nearest neighbor classifier
knniris
- fusion svm_knn the output of svm will be the input of knn classifier
KNN
- Implement the K nearest neighbor algorithm by your own instead of using available software. 2. Use K-fold cross validation to generate training and testing datasets. You should try different K values (3~8) to see how they affect your result. 3. T