提出了一种基于孤立点检测的核聚类入侵检测方法。
An kernel clustering intrusion detection approach based on outlier detection is presented in this paper.
采用核聚类简化的方法降低计算复杂度，提高算法的鲁棒性。
Then the simplified method of kernel clustering was used to reduce the computational complexity and improve the robustness of algorithm.
通过研究核映射机理，提出了用于聚类分析的高斯核聚类算法。
An algorithm of Gaussian kernel clustering is proposed by analyzing kernel mapping theory.
通过研究核聚类算法，以及粗糙集，提出了一个新的用于聚类分析的粗糙核聚类方法。
By means of analyzing kernel clustering algorithm and rough set theory, a novel clustering algorithm, rough kernel k-means clustering algorithm, was proposed for clustering analysis.
文章主要结合商业银行的实际，探讨了核聚类方法在提高银行服务成功率等方面的应用。
In this paper, combining with the commercial Banks' practice, the application of fuzzy kernel C-Means cluster in improving the rate of success in bank services is discussed.
针对模糊核聚类对红外图像分割存在的不足，提出了一种改进的模糊核聚类红外图像分割算法。
Due to the problems of infrared image segmentation using fuzzy kernel clustering, an improved method for infrared image segmentation was proposed.
该方法基于半模糊核聚类算法挖掘不同类别之间的衔接和离散信息，设计树型支持向量机的树型结构，克服其差错积累问题。
The method mines information on overlap between classes, designs the tree structure and overcomes the misclassification of tree-structured SVMs based on the semi-fuzzy kernel clustering algorithm.
研究了具有参数优化的核函数法及其在聚类问题中的应用。
It studies kernel function method with parameters optimized and its application in pattern clustering.
该方法采用核密度估计模型来构造近似密度函数，利用爬山策略来提取聚类模式。
This method USES kernel density estimation model to construct the approximate density function, and takes hill climbing strategy to extract clustering patterns.
提出了基于聚类的核矩阵维度缩减技术。
A novel method for dimensionality reduction of kernel matrix is presented.
首先，运用K-均值聚类方法提取出细胞核，并且采用多域值分割演算法去除细胞图像中的背景区域。
Firstly, nucleus regions of leukocytes in images are automatically segmented by K-mean clustering method. Then single leukocyte region is detected by utilizing thresholding algorithm segmentation.
在分析核方法的核心概念基础上，提出了一种基于核方法的聚类算法。
Based on the analysis of the core concepts of the kernel methods, a clustering algorithm based on kernel methods was put forward.
针对间歇生产过程的配方缺少定量分析方法，难以用于过程建模和控制策略实施的问题，提出了一种基于类核函数的配方模糊聚类算法。
This paper presents a new fuzzy cluster analysis method for batch process recipe that has less quantitative analysis ways before and is difficult to be used for modeling or controlling system.
SVC算法中的核函数参数对聚类的形成起着决定性的作用，并影响着聚类的边界和形状。
Kernel parameter of the SVC algorithm plays an important role in clustering formation, which affects the boundary and shape of cluster.
在子空间聚类引入核函数以提高数据聚类性能。
Kernel function is introduced to subspace clustering to improve the clustering performance.
支持向量聚类是基于支持向量机和核方法的一种新颖的聚类方法。
Rough set was applied to clustering method in view of soft kernel of support vector clustering(SVC).
支持向量聚类是基于支持向量机和核方法的一种新颖的聚类方法。
Rough set was applied to clustering method in view of soft kernel of support vector clustering(SVC).
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