搜索资源列表
tiqubeijing
- 对叶片进行预处理和提取部分特征:1.均值去噪 2.k均值聚类提取复杂背景下的叶子图片 3.填充孔洞 4.去叶柄 5.提取轮廓 6计算纵横轴比、面积凹凸比、周长凹凸比、球形性、圆形性、偏心率、形状参数和矩形度等特征值并进行画图。- Pretreatment of leaves and extract some of the characteristics: a mean denoising 2.k means clusterin
Kjunzhi
- k均值算法,对一组三维数据进行K均值聚类分析,分为三类-k-means algorithm, a set of three-dimensional data of K-means clustering analysis, divided into three categories
2011302590136
- 遥感原理实习,K均值分类,以及图像基本操作,打开保存等-Remote Sensing Principles internship, K-means classification, and image basic operations, such as open saved
ISODATAaKmeans
- 模式识别中经典分类算法——K均值和ISODATA(迭代自组织数据分析算法)的C/C++代码-K-means and Iterative Selforganizing Data Analysis Techniques Algorithm in Pattern Recognition
kmean112233
- 用K均值聚类,不错的程序,可以直接运行的程序-K-means clustering, a good program, you can run the program directly
GXMviv-ImageFusion
- 实现了影响融合的HIS变换算法,小波变换算法和相关系数加权融合。另外还写了k均值分类算法的程序。-Image Fusion
LSSVM
- 最小二乘支持向量机的单模型建模和基于K均值聚类的多模型建模-A single model of least squares support vector machine (SVM) modeling and modeling based on k-means clustering model
isodata22
- isodata算法的matlab实现,其中还附带K均值算法的源码实现。提供数据供大家验证-isodata algorithm matlab implementation, which also comes with K-means algorithm source code implementation. Provides data validation for everyone
K_AVERAGE
- 模式识别K均值处理,程序经过自己修改,可以运行-Pattern Recognition K-means treatment program after their changes, you can run
Kjunzhi
- K均值聚类。加深对K均值聚类分析算法的理解,掌握K 均值聚类分析分类器的设计方法。-K-means clustering. Deepen the K-means clustering algorithm to understand and master K-means clustering analysis classifier design method
Kmeans
- 自适应K-均值聚类算法,能够随着聚簇数目的变化而自动调整聚类数,以最合适的聚簇数目来进行数据分类。-Adaptive K-means clustering algorithm, the number can be clustered with the changes in the number of clusters is automatically adjusted to the most appropriate number for
Untitled1
- 聚类算法举例,初学K-均值算法,应用实例说明算法如何实现。-Clustering algorithm, for example, novice K-means algorithm, application examples illustrate how to implement the algorithm.
cppVersion
- 模式识别C++ K均值算法,采用容器,对数据进行分类-k_means arithmetic
K_average
- K-均值聚类算法,基本算法代码,算法的目的是使各个样本与所在类均值的误差平方和达到最小。-The purpose of K-means clustering algorithm, the basic algorithm code, the algorithm is to make the class where each sample mean squared error is minimized.
kmean
- K均值分类,适合一维或者多维数据,自动识别,分类的数目也可以选择-Kmeans translate
KMeans
- K-均值聚类算法,属于无监督机器学习算法,发现给定数据集的k个簇的算法。 首先,随机确定k个初始点作为质心,然后将数据集中的每个点分配到一个簇中,为每个点找距其最近的质心, 将其分配给该质心对应的簇,更新每一个簇的质心,直到质心不在变化。 K-均值聚类算法一个优点是k是用户自定义的参数,用户并不知道是否好,与此同时,K-均值算法收敛但是聚类效果差, 由于算法收敛到了局部最小值,而非全局最小值。 K-均值聚类算法的一个
Demo_SVM_AdaptiveScale
- 自适应支持向量机应用案例,采用K均值等方式,适用于初学及应用。-Adaptive SVM for learning and application
program
- 包括emd分解程序,求边际谱程序,hilbert包络解调程序,求取小波包频带能量程序,K均值聚类程序-fault diagnosis program
kmedoids1
- matlab下的k中心点聚类算法,matlab内置仅有k均值聚类算法-k under the center clustering algorithm matlab, matlab built-k-means clustering algorithm only
main
- 在MATLAB中,用K均值算法对一些点进行分类,并通过图形进行显示-In MATLAB, using K-means algorithm to classify some point, and through the graphical display