k-mean的例句大全

In this dissertation, adopting the results acquired by the band selection of hyperspectral image based on ACO, the feature bands are extracted as simulation data, and the clustering method experiment is performed. The experiment results are compared with the results of traditional k-means algorithm.

本文依据基于蚁群算法的高光谱图像波段选择方法获得的选择结果，从中提取若干个特征波段作为数据源，采用上述聚类方法进行实验，并与传统的k均值算法比较实验结果。

The new algorithm is to firstly divide unlabeled data into many subsets with a new label by k-means clustering, then train the SVMs using the new data set to get decision boundary and support vectors, at last use the SVMs classifier to classify the unlabeled data.

首先利用k均值算法将未知数据划分成某个数量的子集，然后对新数据进行支持向量机训练得到决策边界与支持矢量，最后对无标识数据进行分类。

Consider water level of boiler drum as the object for study, find out the proper variables as input of the ANN ( Artificial Neural Network) throughout the analysis of the inner mechanism. The function of learning was realized using K-means Cluster method and Gradient Descent Algorithm.

以汽包水位为对象.结合机理分析确定原始变量作为神经网络的输入.通过k均值聚类法则与梯度下降法实现了网络的学习功能.并最终建立了基于RBF神经网络的软测量模型。

Introducing and analyzing k-means algorithms of clustering algorithms and Naive Bayesian Classifier algorithm.

介绍分析聚类分析中的k-means算法和朴素贝叶斯分类算法；

The local searching ability of k-means algorithm is exerted, and the precise of Naive Bayesian Classifier improved. It can solve classification problem effectively.

借鉴K-means算法，用朴素贝叶斯分类算法来解决分类问题，既能发挥K-means算法的局部搜索能力，又能提高朴素贝叶斯分类的准确度，从而更好地解决分类问题。

With respect to the precision and recall of clustering, the experiments indicate that the proposed algorithm is with better performance than the standard ant clustering algorithm and the k-means algorithm.

结果证明本文所提出的基于本体的扩展算法在聚类精度和召回率上优于标准的蚁群聚类算法，达到了算法改进的目的。另外通过与K-means算法的结果比较也显示了本文算法的优越性。

A double k-mean clustering algorithm for modeling and clustering the gene sequence data is proposed by using the hidden Markov models ( HMMs).

本文提出了一种基于隐马尔可夫模型的二次k-均值聚类算法并实现了对基因序列数据的建模与聚类。

Firstly, we use the variant of K-means obtain the basis vectors from the training data, then extract character feature by combining convolutional neural network. 2.

我们先利用改进的K-means聚类方法从训练数据中获得基向量，再结合卷积神经网络提取字符图像的特征。

First, data are pretreated through K-means clustering. Then, attributes are reduced by using rough sets. At last, SVM diagnoses default.

这种方法首先利用K均值聚类对数据进行预处理，然后利用粗糙集对属性进行约简，最后再用支持向量机进行故障诊断。

Experiment shows that the performance of the N-grams phrases method is better than k-means and AHC, not only in the aspect of precision rate and recall rate but also in the aspect of F-measure and time-consuming of clustering.

通过实验对比，N-grams短语方法无论在查准率、查全率，还是F值、聚类用时，都比k-均值算法和AHC算法有更好的性能表现。

The experiment results show that, when the structure of RBF network is definite, gradient-descent method can contribute good performance, while k-means and OLS algorithms are poor in training RBF network for our purpose.

实验结果表明，在RBF神经网络的结构已定情况下，不宜使用k－均值法及.OLS算法，而应该使用梯度下降法。

Studies the Apriori algorithm, BP algorithm and K-means algorithm in this system specific application. Realize the auxiliary teaching system resources allocation around the needs of students to configuration, and support individual learning needs of students.

研究了Apriori算法、BP算法以及K-means算法在该系统的具体应用，从而实现辅助教学系统的资源围绕学生的需求来配置，支持学生的个性化学习需要。

As a classical method of clustering analysis, K-means has been widely used in market analysis, biology, commerce, text classification and so on.

K-means算法作为聚类分析中的经典算法现已被广泛应用在商务、市场分析、生物学、文本分类等领域。

For the segmentation of digital human color slice images, an algorithm based on the theory of connected component labeling in combination with K-mean clustering was proposed.

针对数字人脑彩色切片图像，本文提出了一种连通域标记结合K-均值聚类的分割方法。

K-Mean Cluster Particle Swarm Optimization Algorithm Based on Self-adaptive Chaotic Mutation

基于自适应混沌变异的k-均值聚类粒子群算法

A Double k-Mean Clustering Algorithm for Sequential Gene Data Based on the Hidden Markov Model

基于隐马尔可夫模型的二次k-均值基因序列聚类算法

The fast K-mean image segmentation algorithm based on the grey histogram

基于灰度直方图的快速K-MEAN图象分割算法

K-mean algorithm for optimizing the number of clusters based on particle swarm optimization

基于微粒群优化聚类数目的K-均值算法

Micrograph Segmentation of Chinese Traditional Medicine Lamina Based on K-mean Clustering Algorithm

基于K-均值聚类算法的中药叶片显微图像分割

K-mean distance outlier factor detect for outlier pattern of time series

时间序列异常模式的k-均距异常因子检测