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matlab-code
- 模式识别c均值聚类，也陈k均值，是模式识别中最最要的聚类方法之一。-Pattern Recognition, c-means clustering, and Chen k means, is far the most to the clustering pattern recognition methods.
Combining-face-detection-and-people-tracking-in-v
- Face detection algorithms are widely used in computer vision as they provide fast and reliable results depending on the application domain. A multi view approach is here presented to detect frontal and profile pose of people face using Histogram of
Km
- In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data space into Vo
9552010E202
- This paper presents a new cluster validity index for nding a suitable number of fuzzy clusters with crisp and fuzzy data. The new index, called the ECAS-index, contains exponential compactness and separation measures. These measures indicate ho
clustersuvey
- 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
K-nearest-neighbors
- K MEAN CLUSTERING FOR IMAGE PROCESSING
V7
- Detection of viruses in tomatoes leaf based on K-Mean clustering algorithm-Detection of viruses in tomatoes leaf based on K-Mean clustering algorithm
Detection-of-viruses-in-tomatoes-leaf-based-on-K-
- Detection of viruses in tomatoes leaf based on K-Mean clustering algorithm
k-junzhi
- 通过对K-均值算法的编程实现，加强对该算法的理解和认识。提高自身的知识水平和编程能力，认识模式识别在生活中的应用。 算法思想K-均值算法的主要思想是先在需要分类的数据中寻找K组数据作为初始聚类中心，然后计算其他数据距离这三个聚类中心的距离，将数据归入与其距离最近的聚类中心，之后再对这K个聚类的数据计算均值，作为新的聚类中心，继续以上步骤，直到新的聚类中心与上一次的聚类中心值相等时结束算法。-By programming K- means algorithm implementation, s