搜索资源列表
classification
- 一些典型的模式分类及聚类方法 包括k均值 FDA PCA LMS 贝叶斯 K近邻-The typical pattern classification and clustering methods including k-means FDA PCA LMS Bayesian K-nearest neighbor
Signature-recognition-system
- 模式识别-手写签名识别系统识别!使用K近邻,Bayes分类!-Pattern recognition- recognition of handwritten signature recognition system! Using the K-nearest neighbor and Bayes classification!
K_Average
- 通过k-近邻法将点分成两类,错误率较低,该方法效果挺好-Through the k- neighbor method will point is divided into two kinds, the error rate is low, the method effect is good
QCKNN
- 基于MD-CKNN算法的连续K近邻查询系统,与传统的Find-NN算法进行性能对比-MD-CKNN algorithm-based continuous K-nearest neighbor query system, its performance is compared with traditional Find-NN algorithm
PCA_KNN
- 主成分分析特征提取,K近邻目标识别(针对图像)。-The principal component analysis feature extraction, the K neighboring target recognition (for images).
KNN-matlab
- k近邻的两种改进算法,采用matlab实现,使得算法效率有了较大提高。-two methods for knn,both of them are run in matlat.
KNN
- 模式识别大作业K近邻算法(KNN)C++实现,内有iris和wine数据测试以及其他相关资料。-, Pattern Recognition large job K nearest neighbor algorithm (KNN) C++ achieved within the iris and wine data testing and other relevant information.
kNN
- 用matlab实现K近邻算法,用于数据挖掘的分类-K-nearest neighbor algorithm for the classification of data mining using matlab
srknn
- 自己用matlab编写实现的一个k近邻算法,并有训练和测试数据,能运行。附有注释,简单清晰。-a k-nearest neighbour algorithm developped using matlab.
Classification
- VC++中实现K近邻分类方法,实验数据是著名的iris数据库,此方法是数据挖掘,机器学习,人工智能等课程中重要的分类算法。-K-nearest neighbor classification VC++, experimental data is the famous iris databases, data mining, machine learning, artificial intelligence courses classification algorithm.
nn
- 最近邻算法实现 k近邻 Z为训练集,每行一个样本,n*m labZ为与Z对应的类别,列向量 Z_T为测试集,每行一个样本,p*m labZ_T为输出结果,p*1-Nearest-neighbor algorithm
fcm
- fcm 聚类两个k近邻算法,k近邻的非正式描述,就是给定一个样本集exset,样本数为M,每个样本点是N维向量,对于给定目标点d,d也为N维向量,要从exset中找出与d距离最近的k个点(k<=N),当k=1时,knn问题就变成了最近邻问-fcm cluster
Coordinate
- 基于R树的K近邻查询算法及递增的k近邻查询算法实现-the implemention of R-tree K-nearest neighbor query algorithm and incremental nearest neighbor query algorithm
wine_class
- 借助于k-近邻算法,实现对酒品质的鉴定。并在算法中采用k值的调整以求结果更优。-By means of a k-nearest neighbor algorithm, identification of the quality of the wine. And k values used in the algorithm to adjust in order to better results.
floaterK1
- 这是用MTTLAB编程,采用K近邻法对提取的水面漂浮物特征进行分类-This is programming MTTLAB, K-nearest neighbor method floats feature to classify the extracted water
KNNC
- 使用K近邻算法分类的代码,可返回分类的识别率-KNN Classification
knnsearch
- 一个小而有效的程序来执行的K近邻搜索算法, 非常适合对K -近邻搜索算法的入学者。-A small but effective procedures to implement the K-nearest neighbor search algorithm is very suitable for K- nearest neighbor search algorithm admission
LDA
- LDA:线性判别分析方法。用于实现线性数据降维。采用K近邻分类器对数据进行分类-LDA: linear discriminant analysis method. Used to achieve linear data dimensionality reduction. Using K-nearest neighbor classifier for data classification
kNN_python
- python实现机器学习之k近邻算法,里面附有相关数据文件-kNN arithmetic for python
classifier
- 用matlab实现Part1. 实现一个k近邻分类器,Part 2.实现一个最小二乘分类器,Part 3.实现一个支持向量机分类器,Part 4.在不同数据集上使用交叉验证选择各个算法的参数-Part1. Achieve a k-nearest neighbor classifier, Part 2. Achieve a least-squares classifier, Part 3. Implement a support vector machine classifier, Part 4.