Journal ArticleDOI
A simple and fast algorithm for K-medoids clustering
Hae-Sang Park,Chi-Hyuck Jun +1 more
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TLDR
Experimental results show that the proposed algorithm takes a significantly reduced time in computation with comparable performance against the partitioning around medoids.Abstract:
This paper proposes a new algorithm for K-medoids clustering which runs like the K-means algorithm and tests several methods for selecting initial medoids. The proposed algorithm calculates the distance matrix once and uses it for finding new medoids at every iterative step. To evaluate the proposed algorithm, we use some real and artificial data sets and compare with the results of other algorithms in terms of the adjusted Rand index. Experimental results show that the proposed algorithm takes a significantly reduced time in computation with comparable performance against the partitioning around medoids.read more
Citations
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Journal ArticleDOI
Spectrum Sharing in mmWave Cellular Networks Using Clustering Algorithms
Ning Xie,Le Ou-Yang,Alex X. Liu +2 more
TL;DR: This paper proposes two spectrum sharing schemes for the mobile scenario and the stationary scenario, respectively, based on the SCA-OPM scheme andSCA-SSB scheme, which effectively saves the overall overhead and complexity.
Journal ArticleDOI
Ensemble summarization of bio-medical articles integrating clustering and multi-objective evolutionary algorithms
TL;DR: The proposed ensemble method is compared with some state-of-art methods to demonstrate that it is both effective and statistically significant.
Journal ArticleDOI
CATBOSS: Cluster Analysis of Trajectories Based on Segment Splitting.
TL;DR: In this paper, a new method, cluster analysis of trajectories based on segment splitting (CATBOSS), applies density-peak-based clustering to classify trajectory segments learned by change detection.
Dissertation
Automatic clustering with application to time dependent fault detection in chemical processes
Journal ArticleDOI
LTE-LAA cell selection through operator data learning and numerosity reduction
TL;DR: In this article , the effect of cell selection on LTE-LAA capacity and network feature relationships is investigated through operator data analysis, and two state-of-the-art cell association and resource allocation solutions are implemented.
References
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Some methods for classification and analysis of multivariate observations
TL;DR: The k-means algorithm as mentioned in this paper partitions an N-dimensional population into k sets on the basis of a sample, which is a generalization of the ordinary sample mean, and it is shown to give partitions which are reasonably efficient in the sense of within-class variance.
Journal ArticleDOI
Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
TL;DR: A new graphical display is proposed for partitioning techniques, where each cluster is represented by a so-called silhouette, which is based on the comparison of its tightness and separation, and provides an evaluation of clustering validity.
Book
Finding Groups in Data: An Introduction to Cluster Analysis
TL;DR: An electrical signal transmission system, applicable to the transmission of signals from trackside hot box detector equipment for railroad locomotives and rolling stock, wherein a basic pulse train is transmitted whereof the pulses are of a selected first amplitude and represent a train axle count.
BookDOI
Finding Groups in Data
TL;DR: In this article, an electrical signal transmission system for railway locomotives and rolling stock is proposed, where a basic pulse train is transmitted whereof the pulses are of a selected first amplitude and represent a train axle count, and a spike pulse of greater selected amplitude is transmitted, occurring immediately after the axle count pulse to which it relates, whenever an overheated axle box is detected.