Clustering is the process of grouping or aggregating of data items. Sentence clustering mainly used in variety of applications such as classify and categorization of documents, automatic summary generation, org
Although less straightforward, the performance evaluation on an unsupervised learning model is also important. In this post, I’m going to talk about how to evaluate the performance of a clustering model, a major task in unsupervised learning, if the ground-truth labels are not available. So, ...
Cluster Shared Volumes (CSV) is a new storage architecture in Windows Server 2008 R2 Failover Clustering which functions as a distributed-access file system optimized for Hyper-V Virtual Machines. We have added performance counters for this new technology. This is the only counter set...
InPart 1of this blog series we discussed Performance Counters and their interaction with the Network, Multicast Request Reply, Global Update Manager and Database clustering components. InPart 2we looked at monitoring some additional cluster components: the Checkpoint Manager, R...
This paper proposes a clustering scheme to improve energy efficiency for cluster-based wireless sensor networks (WSNs). In order to reduce the energy dissipation of transmitting sensing data at each sensor, the proposed fixed algorithm uniformly divides the sensing area into clusters where the cluster...
auto_awesome_motion View Active Events Harry Beasley·1y ago· 89 views arrow_drop_up0 Copy & Edit 4 more_vert Runtime play_arrow 23s Language Python
The effect of various AE structures on the clustering performance in terms of accuracy and David Bouldin Index (DBI) has been investigated; The effect of the hyperparameters tuning of the developed DL models on the clustering performance has been investigated and discussed; Finally, to demonstrate ...
The performance can be evaluated in terms of accuracy and validity of the clusters, and also the time required to generate them, using appropriate performance measures. In this paper, we have analysed the performance of Self-Organizing neural network based clustering and k-Means clustering using ...
We show that for any data set in any metric space, it is possible to construct a hierarchical clustering with the guarantee that for every k, the induced k-clustering has cost at most eight times that of the optimal k-clustering. Here the cost of a clustering is taken to be the maximum...
Yang L, Chiu S, Liao W, Thomas M (2013) High performance data clustering: a comparative analysis of performance for GPU, RASC, MPI, and OpenMP implementations. J Supercomput 70(1):284–300Yang, L.; Chiu, S.C.; Liao, W.K.; Thomas, M.A. High Performance Data Clustering: A ...