搜索资源列表
knnsearch
- 一个小而有效的程序来执行的K -近邻搜索算法，此算法利用JIT 理论加速循环，比向量化有效解决了大量数据的精度问题。甚至比kd-tree效果要佳-A small and effective procedures to implement the K- nearest neighbor search algorithm, this algorithm uses JIT acceleration cycle theory, than to solve a lot of data to quantif
kdtree
- 用matlab编写的k-dtree，加快搜索，在点云拼合中应用广泛。-Matlab prepared with k-dtree, to speed up the search, put together in the point cloud in a wide range of applications.
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
Kth_number
- 划分树求区间K小数的Pascal源代码, 其建树复杂度为O（nlogn）, 回答询问为O（logn)-A kind of tree to answer the kth smallest number in an interval.
k-Nearest-Neighbor
- K邻近快速算法，包含有独立的样本分解算法，树搜索算法，稍作改动便可以满足各种要求。-K adjacent fast algorithm contains a separate sample decomposition algorithm, the tree search algorithm, some minor changes will meet a variety of requirements.
Files-and-Codes
- -data mining-Naive Bayesian Classifier -Decision Tree- K--data mining-Naive Bayesian Classifier -Decision Tree- KNN
Three_N_KD
- k-d 搜索，可以搜索大量二维数据点的距离，-k-d tree
kdtree1.2
- Kd-trees are data structures which are used to store points in k-dimensional space. As it follows its name, kd-tree is a tree. Tree leafs store points of the dataset (one or several points in each leaf). Each point is stored in one and only one leaf,
分类器比较
- 支持向量机，线性判别分析，回归树，主成分判别分析，分类回归树，K临近算法(SVMLinear discriminant analysis, regression tree, principal component discriminant analysis, classification regression tree, K proximity algorithm)