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Journal ArticleDOI

A simple and fast algorithm for K-medoids clustering

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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.

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Book ChapterDOI

Cluster Validity Using Modified Fuzzy Silhouette Index on Large Dynamic Data Set

TL;DR: This work proposed approaches to reduce time complexity by modifying fuzzy silhouette index at center to center and center to mean levels to find the right number of cluster and they are giving correct value in minimum execution time.
Proceedings ArticleDOI

Elevator Traffic Pattern Recognition Based on Density Peak Clustering

TL;DR: Experiments show that the method can effectively recognize the elevator traffic pattern, is easy to implement, has fast calculation speed, and has a stable clustering effect, and can meet the real-time requirements of the group control system.
Book ChapterDOI

Highly Reproducible Whole Brain Parcellation in Individuals via Voxel Annotation with Fiber Clusters

TL;DR: In this article, the authors parcellate the brain into coherent parcels using non-negative matrix factorization based on voxel annotation using fiber clusters, which is shown to be highly reproducible with 100% test-retest parcel identification rate and significantly lower inter-subject variability than FreeSurfer parcellation.
Proceedings ArticleDOI

Clustering Aircraft Trajectories According to Air Traffic Controllers' Decisions

TL;DR: A step in the direction of data-driven analysis is taken by clustering trajectories according to air traffic control decisions (e.g. trajectory changes), as opposed to clustering on spatial positioning reports.
Journal ArticleDOI

Visualization and Mapping of Knowledge and Science Landscapes in Expert Systems With Applications Journal: A 30 Years’ Bibliometric Analysis:

TL;DR: The Expert Systems With Applications (ESWA) is a leading journal in the fields of computer science and engineering as discussed by the authors, and it has been used extensively in the field of computer networks.
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.
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