搜索资源列表
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
- knn (k-nearest neighbor)用c++实现的近邻算法-knn (k-nearest neighbor) algorithm
knnsearch
- 寻找测试样本的最近邻，可以有效的用于用于模式识别，信号处理-This is a small but efficient tool to perform K-nearest neighbor search, which has wide Science and Engineering applications, such as pattern recognition, data mining and signal processing. The code was initially
kd-tree
- knn搜索 利用kd tree 查找最相邻的k个高维空间的点-knn kd-tree
kd-Tree-On-KNN
- 利用K_D树数据结构实现K邻域搜索的算法代码-K_D tree data structure the K neighborhood search algorithm code
knn
- KNN分类器的MATLAB代码，速度快效果好，适合初学者使用。-KNN search without using any gancy data structure, such as kd-tree. However, it is the fastest knn matlab implementation I ever found.
KNN Matting
- KNN算法实现的抠图程序，包含数据集，使用了KD树实现KNN(KNN algorithm to achieve the matting process, including data set)
knn-MATLAB
- 这是一个实现简单的多数表决法的KNN算法。KNN算法涉及三个重要的步骤，分别是决定K的大小；距离的表达方法（一般有欧式距离，曼哈顿距离，Minkowski距离）；决策方法（多数表决法，KD树法等）。本程序是采用多数表决的决策方法，距离表达采用欧式距离。适用于小样本少特征的数据集。(KNN algorithm realized by MATLAB, useful for small training set and less features.)