k-mean的例句大全

First, this algorithm assembles task vertex with similar attribute to form a bigger new task vertex based on K-means clustering, and then partitions hardware/ software based on simulated annealing algorithm.

算法首先将有相似属性的任务节点通过K均值聚类算法组成一个大的任务节点，而后使用模拟退火算法划分由大的任务节点组成的系统。

The tread of warrant theoretical price which is calculated by RBF network model based on K-means clustering algorithm 、 gradient descent and particle swarm optimization algorithm and the actual price is same. 3.

基于K-均值聚类算法、梯度下降算法和PSO算法优化的RBF网络模型计算的权证理论价格与实际价格的趋势基本一致。

As k-means clustering applied to divide two-dimensional laser data is worse than dividing one-dimensional and three-dimensional data. The two-dimensional laser data is not ideal after partition.

相对于一维和三维数据的聚类，K均值聚类算法对二维激光数据的聚类划分效果一般，聚类后的数据可能不是理想的效果。

Clustering analysis is an important method in data mining. K-means algorithm is an important clustering method based on partition. It is simple, fast, high efficiency better retractility.

聚类方法是数据挖掘中的一种重要方法，k-means算法是一种重要的基于划分的聚类分析方法，该方法具有简单、快速、高效及可伸缩性强等优点。

Mahout provides driver programs for all of the clustering algorithms, including the k-Means algorithm, aptly named the KMeansDriver.

Mahout为所有集群算法都提供了驱动程序，包括k-Means算法，更合适的名称应该是KMeansDriver。

segmentation strategy on customer behavior of commercial bank retail business in china based on k-means arithmetic

基于K-means算法的中国商业银行零售业务顾客行为细分策略

A New Approach to Ascertain the Initial Clustering Centers of K-means

一种新的确定K-均值算法初始聚类中心的方法

Besides, it is also necessary to find out the central time series in some clustering algorithms, the k-means algorithm, for example.

在一些中心聚类方法中，也必须计算时间序列的中心，例如k-means算法。

Therefore, according to the character of cartridge case images, graph transformation matching, angle or scale constraint using adaptive K-means clustering are respectively applied to remove incorrect matches.

因此，本文依据弹壳图像特点，分别运用了三种去除错误匹配方法：图变换匹配、自适应K-均值聚类的角度约束或尺度约束。

Agglomerative Fuzzy K-means proposed by Li Mark can avoid the problems.

Li Mark提出的凝聚模糊K-means算法可以有效的避免这两个问题。

Outliers detection method based on K-means and agglomerative clustering

基于K-均值聚类和凝聚聚类的离群点查找方法

Camouflage color selection based on improved K-means clustering

基于改进K均值聚类分析的迷彩伪装色选取

the main findings are as follows: ( 1) a synthetic system was established for standard cut chrysanthemum by means of expert consultation, analytic hiberarchy process and k-means cluster method.

主要研究结果如下：（1）利用专家咨询法并结合其他观赏植物评价体系，构建了单头切花菊性状综合评价体系。

The focus segmentation of color ophthalmologic image based on modified k-means clustering and mathematical morphology

基于改进的k-均值聚类和数学形态学的彩色眼科图像病灶分割

Detail compared the image recognition result of the three primary color threshold segmentation, iterative threshold segmentation, K-means clustering segmentation and temperature threshold segmentation in this paper. The analysis shows that temperature threshold segmentaion is superior to the above several other segmentaion scheme.

详细对比了三基色阈值分割、迭代阈值分割、K-means聚类分割以及本文提出的温度阈值分割的图像识别结果，分析结果表明，温度阈值分割优于以上的其它几种分割方案。

Multiscale information fusion halftone method, mixed error measure function of the establishment of multiscale wavelet coefficients fusion to establish the boundary error measure function and improved K-means clustering method to establish the area error metric function.

在多尺度信息融合的半色调方法中，混合误差测度函数的建立是利用多尺度小波系数融合建立的边界误差测度函数和改进的K-means聚类法建立的区域误差测度函数。

Fuzzy K-Prototypes ( FKP) algorithm integrating K-Means and K-Modes algorithm is suited for clustering mixed numeric and categorical valued data.

模糊K Prototypes（FKP）算法融合了k means和k modes对数值型和符号型数据的处理方法，适合于混合类型数据的聚类分析。

In this paper a modified K-means algorithm ( FKM) is presented.

本文提出了一种改进的k means算法（FKM）。

Particle swarm optimization ( PSO) algorithm is adopted to optimize the center of fuzz K-means ( FKM) with kernel function, which is used to classify the temperature of blast furnace.

提出了一种高炉炉温分类辨识的方法PSO-K-FKM，该方法采用基于核函数改进的模糊K均值聚类，利用粒子群对聚类中心寻优。

We isolated error data using k-means algorithm before the data fusion, and then used the least square method to fuse the remaining reliable data.

KLRQP协议首先使用k-均值聚类的方法分离出误差数据。然后，使用最小二乘原理对剩余可靠数据进行融合处理。