Journal ArticleDOI
A simple and fast algorithm for K-medoids clustering
Hae-Sang Park,Chi-Hyuck Jun +1 more
Reads0
Chats0
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
More filters
K-median Algorithms: Theory in Practice
TL;DR: All of the distance metrics satisfy the properties of a metric space, including dij, which is defined as dij is the distance between points i and j in the metric space X.
Journal ArticleDOI
Robust Collaborative Clustering of Subjects and Radiomic Features for Cancer Prognosis
Hangfan Liu,Hongming Li,Mohamad Habes,Yuemeng Li,Pamela Boimel,James Janopaul-Naylor,Ying Xiao,Edgar Ben-Josef,Yong Fan +8 more
TL;DR: A robust collaborative clustering method to simultaneously cluster patients and radiomic features into distinct groups respectively under adaptive sparse regularization built upon matrix tri-factorization enhanced by adaptive sparsity regularization for simultaneous feature dimensionality reduction and denoising.
Journal ArticleDOI
Learning representative exemplars using one-class Gaussian process regression
TL;DR: A novel exemplar learning method using one-class Gaussian process (GP) regression is proposed in this study, which constructs data distribution support from one- class GP regression using automatic relevance determination prior and heterogeneous GP noise.
Journal ArticleDOI
Validation of prediction models of severe disease course and non-achievement of remission in juvenile idiopathic arthritis : part 1-results of the Canadian model in the Nordic cohort
Veronika Gjertsen Rypdal,Jaime Guzman,Andrew Henrey,Thomas M. Loughin,Mia Glerup,Ellen Dalen Arnstad,Ellen Dalen Arnstad,Kristiina Aalto,Marite Rygg,Susan Nielsen,Troels Herlin,Anders Fasth,Lillemor Berntson,Martin Rypdal,Ellen Nordal +14 more
TL;DR: The Canadian prediction model had excellent predictive ability and was comparable in performance to the Nordic model in predicting severe disease course in the Nordic JIA cohort, and it is suggested that predicting long-term remission is more challenging than predictingsevere disease course.
Improving non-linear approaches to anomaly detection, class separation, and visualization
TL;DR: Improvements to existing non-linear techniques are investigated for the purposes of providing better, timely class separation and improved anomaly detection on various multivariate datasets, culminating in application to anomaly detection in hyperspectral imagery.
References
More filters
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.