Description: 将彩色图像从RGB转化到lab彩色空间，进行K-mean聚类将图像分割-The color image in RGB color space conversion to lab space , K-mean clustering image segmentation
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Author:zhangfengyuan |
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Description: kmeans ieee paper , A system for analyzing student’s results based on cluster analysis and uses standard statistical algorithms to arrange their scores data according to the level of their performance is described.
K-mean clustering algorithm for analyzing students’ result data.
-kmeans ieee paper , A system for analyzing student’s results based on cluster analysis and uses standard statistical algorithms to arrange their scores data according to the level of their performance is described.
K-mean clustering algorithm for analyzing students’ result data.
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Size: 798720 |
Author:bala |
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Description: 基于Lab空间向量的图像分割方法，采用k-mean聚类。-Based on the Lab space vector image segmentation method, the use of k-mean clustering. Platform: |
Size: 1024 |
Author:李长生 |
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Description: KNN(K最近邻)分类算法以及K-means(K均值)聚类算法是应用广泛的两种算法。本代码是在VS2010环境下，用 C++语言在基于KNN及K-means算法下，实现了对Iris数据集的分类与聚类。-KNN (K nearest neighbor) classification algorithm, as well as K-means (K mean) clustering algorithm is widely used two algorithms. The code VS2010 environment, with C++ language based KNN and K-means algorithm to achieve the classification and clustering of the Iris data set. Platform: |
Size: 8197120 |
Author:dancy88927 |
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Description: 用于遥感图像分类。其输入为几幅遥感图像，使用k-mean聚类方法对图像中的不同地形进行聚类分割--For remote sensing image classification. Their input for a number of remote sensing images, the use of k-mean clustering method to image the topography of the different cluster partition Platform: |
Size: 193536 |
Author:王斌 |
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Description: 讲解了分层次聚类法、最简单聚类法、最大距离样本、K平均聚类法、叠代自组织聚类法、ISODATA法的改进等-Explain the hierarchical clustering method, the simplest clustering method, the maximum distance the sample, K mean clustering method, self-organizing clustering iterative method, ISODATA method of improvement Platform: |
Size: 47104 |
Author:冯俊惠 |
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Description: 基于聚类的径向基神经网络的设计算法，采用的是K均值聚类。实现函数拟合！-The design algorithm of radial basis function neural network based on clustering, using the K mean clustering. Realize the function fitting! Platform: |
Size: 1024 |
Author:范敬柱 |
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Description: 本代码是基于k-mean聚类的关键帧提取代码，是用matlab来实现的。-The code is based on k-mean clustering key frame extraction code, using matlab to achieve. Platform: |
Size: 1024 |
Author:李亚南 |
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Description: 针对背景差法易受外界环境因素影响的缺点, 提出了一种基于改进K-均值聚类的背景建模方法。通过比较任意样本与该像素位置处的子类中心之间的距离, 对各个像素的观察值进行聚类, 并在聚类过程中逐步确定其类别数。一段时间的学习之后, 样本数最多的子类就构成了背景模型。仿真结果表明, 该算法即使在运动目标存在的情况下也能准确的提取出实际的
背景, 而且显著地降低了系统的存储量。-Aimed at the disadvantage that background subtraction was liable to be affected by outside environment,
a background modeling method based on the improved K-mean clustering was provided. By comparing the distances
between certain sample and sub-class center of the pixel, observation values of the pixels were clustered and the
number of the clusters was determined during the clustering process.. After learning for a period, background model
was built by sub-class with the maximum samples. Simulations show that actual background can be extracted accurately
by the algorithm even when moving targets are existent and the memory cost of the system is reduced dramatically Platform: |
Size: 1495040 |
Author: |
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Description: Detection of viruses in tomatoes leaf based on K-Mean clustering algorithm-Detection of viruses in tomatoes leaf based on K-Mean clustering algorithm Platform: |
Size: 1213440 |
Author:mokhtar |
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Description: 聚类算法中的k-means算法，和k-medoids 肯定是非常相似的。k-medoids 和 k-means 不一样的地方在于中心点的选取，在 k-means 中，我们将中心点取为当前 cluster 中所有数据点的平均值。-Clustering algorithm k-means algorithm, and k-medoids certainly very similar. k-medoids and k-means not the same place that the center of the selection, the k-means, we will take the average of the center point of all the data points in the current cluster. Platform: |
Size: 22528 |
Author:赵小娟 |
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Description: K_Mean聚类分析算法用于各地区城镇居民年人均收入的分析（分别4类），包括原始数据以及代码！结果在Data1、Data2、Data3、Data4中.-K Mean clustering algorithm used to analyze the regional urban residents per capita income (Class 4, respectively), including the original data and code! Result in Data1, Data2, Data3, Data4 in. Platform: |
Size: 9216 |
Author:刘韬 |
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Description: 本书第一部分主要介绍机器学习基础，以及如何利用算法进行分类，并逐步介绍了多种经典的监督学习算法，如k近邻算法、朴素贝叶斯算法、Logistic回归算法、支持向量机、AdaBoost集成方法、基于树的回归算法和分类回归树（CART）算法等。第三部分则重点介绍无监督学习及其一些主要算法：k均值聚类算法、Apriori算法、FP-Growth算法。第四部分介绍了机器学习算法的一些附属工具。-
In the first part, mainly introduced the machine learning base, and how to use the algorithm to classify, and gradually introduced the variety of classical supervised learning algorithms such as k-nearest neighbor, naive Bayes algorithm, logistic regression algorithm, support vector machine (SVM) and AdaBoost ensemble method, based on the regression tree algorithm and classification and regression tree (CART) algorithm. The third part focuses on unsupervised learning and some of the main algorithms: K mean clustering algorithm, Apriori algorithm, FP-Growth algorithm. The fourth part introduces some tools of machine learning algorithm. Platform: |
Size: 20149248 |
Author:孙伟 |
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Description: k-mean聚类算法。最简实现，全部做了中文注释-K-mean clustering algorithm. The simplest implementation, all done in Chinese Notes Platform: |
Size: 3072 |
Author:jacky |
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Search - k-mean clustering