搜索资源列表
k-means
- 简单的k-means算法 简单的实现简单数据的分类。-Simple k-means algorithm is simple to achieve the classification of simple data.
k-means-
- 这个文档提供了几种k-means算法的改进流程图与思路-This document provides an improvement of several k-means algorithm flowchart and ideas
K-Means-GA
- k-menas using genetic algorithm for centroid initialization
k-means-php
- k-means algorithm using php
L-K
- opencv 下实现的L-k光流估算模型。有利于理解l-k光流、-the opencv achieved under the Lk optical flow estimation model. Conducive understanding lk optical flow,
K-SVD-dictionary-training-algorithms
- 基于KSvd算法的图像重建，包括图像、代码、字典等-K-SVD dictionary training algorithms
K-Meansl
- 自己编写了一个c++的k均值聚类算法，使用起来很方便，数据存储在txt文件里，可以 改成自己的数据，方便使用,目录里给了两组UCI机器学习数据库上的数据，供实验用 。可以用这个文件直接运行就好了，里面给出了详细的使用说明。-k means clustering by array.
K-Lface-recognition
- 基于K-L变换的人脸识别技术 包括人脸的重建 K-L计算 大家可以参考下-Based on KL Transform for Face Recognition technology including the reconstruction of the face KL calculation we can refer to
K-match
- K-近似匹配，动态规划法。输入两个文本和编辑距离k，找出k以内的文本匹配情况。代码很短短，没有相当算法功底很难看懂。最好参考经典的算法设计书籍。-K-approximate matching, dynamic programming method. Two input text and edit distance k, find k within the text to match. The code is a short, not quite algorithms foundation is
find--k-best-1.00
- Implementation of the Murty algorithm to obtain the best K assignments. Includes the implementation of the Jonker-Volgenant algorithm. Usual applications are multiple target tracking algorithms, Joint Probabilistic Data Association (JPDA), Mult
K-means
- 模式识别中聚类分析经典算法，K-均值算法，C语言编写，可以读入文件，处理任意维数和任意个数的特征向量，附有测试数据。-The classic pattern recognition, cluster analysis algorithm, the K-means algorithm, written in C language, can read the file, handle any number of dimensions and any number of feature vectors
K-expected
- 这是K—均值二维算法的C++实现，模式识别用的-This is a two-dimensional algorithm of K-means C++ achieved, and pattern recognition with
k-means
- k均值算法，一种聚类算法，用来实现网络上相近节点的映射。-k-means algorithm, a clustering algorithm, used to achieve similar nodes in the network mapping.
K-negibour-method
- 利用K近邻法实现数字识别算法。误差小，识别效率高，网络训练速度快。-K-nearest neighbor algorithm, digital identification algorithm. Error is small, high recognition efficiency and speed of network training.
K-means
- K-means算法是很典型的基于距离的聚类算法，采用距离作为相似性的评价指标，即认为两个对象的距离越近，其相似度就越大。这是一本介绍K-means算法的英文书籍 -K-means algorithm is very typical distance-based clustering algorithm, using distance as the similarity evaluation, that the closer the two objects, the greater the s
k-and-isodata
- 模式训别的k均值算法和isodata聚类算法c++实现，程序有较清楚的注释，且有word文档说明程序是如何实现算法的，对于刚接触模式识别的程序具有很好的启发作用，不足之处是没有用mfc完成界面编程-Mode of training to achieve other k-means algorithm and isodata clustering algorithm c++, procedures clearer notes and word documents that the program
K-MEANS
- 简单的K均值聚类函数，用于求算重心的函数，算法高效快速-Simple K-means clustering function for calculating the center of gravity function, the algorithm is fast and efficient
k-means
- 数据挖掘-聚类分析：k-平均(k-Means)算法实现（C++） -Data Mining- Cluster Analysis: k-average (k-Means) algorithm (C++)
K-means-and-Perceptron
- 该程序为matlab程序，共有三个文件，dataC.m为程序入口，实现功能对50组数据用k均值算法进行分类，再对40组数据用感知器算法训练，然后用训练得到的判别函数对剩下10组数据分类，最后与原始分类做差比较，若分类无误，则全显示为0.-Matlab program on the program, a total of three files dataC.m for program entry features 50 sets of data with k-means algorithm to
K-means
- k均值聚类算法,初始随机给定k个簇中心，根据邻近原则，把待分类的样本点分到各个簇。-k-means clustering algorithm,which is applied in RBF neural network.