These two algorithms are supported by a clustering-based method to compute an initial solution of the problem, which yields an upper bound of the number of locations needed to solve the problem. We propose a grid partitioning-based strategy to refine the initial solution and obtain the final ...
A clustering based method to solve duplicate tasks problem一种利用聚类思想解决重复任务问题的处理方法181流程挖掘重复任务聚类流程挖掘是一种从实际业务执行日志中发现结构化流程信息的过程.流程挖掘技术广泛应用于业务流程的发现和辅助建模过程中,并能够通过差异分析的方法帮助改进已有业务流程.如何处理流程模型中的重复...
As a reference, we also checked the dependency of a clustering-based method on the number of clusters predicted in a dataset (Supplementary Fig. 7E). Compared with the dependency of cluster-based approaches on the number of predicted clusters, singleCellHaystack is relatively stable w.r.t. ...
Moreover, a Clustering method based on the HKNN graph (CHKNN) is proposed. The CHKNN first generates several tight and small subclusters, then merges these subclusters by exploiting the connectivity among them. In order to select the optimal parameters for CHKNN, we further propose an ...
The method can also be used to represent the consensus over multiple runs of a clustering algorithm with random restart (such as K-means, model-based Bayesian clustering, SOM, etc.), so as to account for its sensitivity to the initial conditions. Finally, it provides for a visualization ...
A clustering-based method for unsupervised intrusion detections Pattern Recogn. Lett., 27 (2006), pp. 802-810 View PDFView articleView in ScopusGoogle Scholar [22] Y. Yang, J. Jiang Hybrid sampling-based clustering ensemble with global and local constitutions IEEE Trans. Neural Networks Learn....
A Clustering‐Based Evidence Reasoning Method Aiming at the counterintuitive phenomena of the Dempster鈥揝hafer method in combining the highly conflictive evidences, a combination method of evidences b... X Li,F Wang - 《International Journal of Intelligent Systems》 被引量: 3发表: 2016年 Assessment...
6 . 2 boosting as a kernel-based method in this section, we give a basic overview of boosting, and present the boosting kernel. 2.1 boosting: notation and overview assume we are given a model \(g(\theta )\) for some observed data \(y\in {\mathbb {r}}^n\) , where \(\theta \...
It is an effective method to discover the underlying patterns in unlabeled data [1]. The primary purpose of all the clustering algorithms is to divide the elements of data into groups/clusters based on some similarity between the data elements, with an aim to discover the underlying patterns. ...
This repository accompanies “Shape-Based Clustering of Daily Weigh-In Trajectories using Dynamic Time Warping”. The aim of the paper was to use Dynamic Time Warping, a shape-based clustering method, to cluster binary trajectories and evaluate patterns.