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
Transforming a Patient Registry Into a Customized Data Set for the Advanced Statistical Analysis of Health Risk Factors and for Medication-Related Hospitalization Research: Retrospective Hospital Patient Registry Study.
Zhivko Taushanov,Henk Verloo,Boris Wernli,Saviana Di Giovanni,Armin von Gunten,Filipa Pereira +5 more
TL;DR: The methods used to transform and synthesize a raw, multidimensional, hospital patient registry data set into an exploitable database suitable for an advanced analysis of the descriptive, predictive, and survival statistics relating to polymedicated, home-dwelling older adults admitted as inpatients are described.
Proceedings ArticleDOI
Is My Object in This Video? Reconstruction-based Object Search in Videos
TL;DR: This paper addresses the problem of video-level object instance search, which aims to retrieve the videos in the database that contain a given query object instance, and proposes the Reconstruction-based Object SEarch (ROSE) method, which characterizes a huge corpus of features of possible spatial-temporal locations in the video into the parameters of the reconstruction model.
Journal ArticleDOI
Fast Co-MLM: An Efficient Semi-supervised Co-training Method Based on the Minimal Learning Machine
TL;DR: This paper proposes an improved variant of Co-MLM with reduced computational cost on both training and testing phases, and is compared to Co- MLM and other Co-training-based semi-supervised methods, presenting comparable performances.
Journal ArticleDOI
On representative day selection for capacity expansion planning of power systems under extreme operating conditions
TL;DR: In this paper, an input-based and a cost-based approach in combination with the k-means and the k -medoids clustering algorithms for representative day selection is presented.
Journal ArticleDOI
Clustering Indoor Positioning Data Using E-DBSCAN
TL;DR: A new method called E-DBSCAN is proposed, which extended DBSCAN to trajectory clustering of indoor positioning data, and a Weighted Edit Distance algorithm was proposed to measure the similarity of the trajectories.
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.