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c++实现的KNN库:建立高维度的K-d tree
- c++实现的KNN库:建立高维度的K-d tree,实现K邻域搜索，最小半径搜索-K-NN algorithm implementation. It supports data structures and algorithms for both exact and approximate nearest neighbor searching in arbitrarily high dimensions.
kNN
- k Nearest Neighbor matlab code
kmeansclustering
- K means clustering using php.
KNN
- KNN clustering with php
tf
- EM聚类算法，Knn分类算法简单C++编程-EM clustering algorithm, Knn classification algorithm is simple C++ programming
KNN
- 这是一个KNN聚类程序，大家共同学习,希望对大家有帮助!-This is a KNN clustering procedure, we learn together, we hope there is help!
svm
- 本程序包括：论文SVM 用于基于块划分特征提取的图像分类，和相应的matlab实现其中图像划分以及特征提取、聚类均利用matlab6.5完成。 -The procedures include: paper by SVM for feature extraction based on block classification, and the corresponding realization of one image into matlab, and feature extraction,
Knn
- MATLAB 聚类和近邻搜索模块代码如下-MATLAB clustering and nearest neighbor search module code is as follows
TCM-NN-Algorithm
- TCM-KNN 算法 用于聚类分析 Debug内包含txt格式dataset 以及测试数据 程序可实现 对测试数据的自动分类-TCM-KNN algorithm for clustering analysis Debug txt format dataset contains data and test procedures can be realized on the automatic classification of test data
Wavelet-P-Svd-age-determination
- Its a method where we have used wavelet and svd method to estimate the age of digital fingerprint using knn clustering method.
lm
- 各种对图像的分类和聚类的方法，kmeas、knn、pca等，还有几种数据处理中的窗函数-Variety of image classification and clustering methods, kmeas, knn, pca, etc., there are several data processing window function
KNN
- knn聚类算法的python描述，兼容python2.7 3.0以上版本-python knn clustering algorithm descr iption, compatible python2.7 3.0 or later
kNN
- knn算法。成名的k紧邻算法，聚类算法，可以用作分类。希望帮到大家。-knn algorithm. K close to the famous algorithm, clustering algorithm, it can be used as a classification. We hope to help everyone.
KNN
- K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering metho
knn1
- K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering metho
kmediod
- k-mediod、knn、uci数据集。 数据挖掘、机器学习中的经典聚类、分类算法(K-mediod, KNN, and UCI data sets. Data mining and classical clustering and classification algorithms in machine learning)
Clustering
- 本代码实现多个方法对数据进行聚类，例如knn方法(This code implements multiple methods to cluster data, such as the KNN method)
K-Means Clustering menggunakan Matlab
- knn image recognition for matlab code
kNN
- 机器学习/python入门项目一：聚类kNN(Machine learning / python entry project: clustering kNN)
matlab代码
- Matlab代码，根据算法原理自己编写的基本算法的代码，有：KNN，层次聚类，C均值，最邻近算法。包括自己挑选的数据集，对算法准确率的测试。(Matlab code, the code of the basic algorithm written by itself according to the algorithm principle, there are: KNN, hierarchical clustering, C-means, nearest neighbor algorithm.