Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics [PDF]
, 2013 Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper,
A Su +39 more
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Galaxy Cluster Correlation Function to z ~ 1.5 in the IRAC Shallow Cluster Survey [PDF]
, 2007 We present the galaxy cluster autocorrelation function of 277 galaxy cluster candidates with 0.25 \le z \le 1.5 in a 7 deg^2 area of the IRAC Shallow Cluster Survey.
A. H. Gonzalez +9 more
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Improving Image Clustering through Sample Ranking and Its Application to Remote Sensing Images
Remote Sensing, 2022 Image clustering is a very useful technique that is widely applied to various areas, including remote sensing. Recently, visual representations by self-supervised learning have greatly improved the performance of image clustering.
Qinglin Li, Guoping Qiu
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OSSOS VI. Striking Biases in the detection of large semimajor axis Trans-Neptunian Objects [PDF]
, 2017 The accumulating, but small, set of large semi-major axis trans-Neptunian objects (TNOs) shows an apparent clustering in the orientations of their orbits.
Alexandersen, Mike +11 more
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Density Peak Clustering Based on Relative Density under Progressive Allocation Strategy
Mathematical and Computational Applications, 2022 In traditional density peak clustering, when the density distribution of samples in a dataset is uneven, the density peak points are often concentrated in the region with dense sample distribution, which is easy to affect clustering accuracy.
Yongli Liu, Congcong Zhao, Hao Chao
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An Improved DGA Feature Clustering-Based Method for Transformer Fault Diagnosis
CSEE Journal of Power and Energy SystemsThe power transformer is the core equipment of a power system, and its reliable operation is crucial for maintaining the safety and stability of power grids.
Yujie Zhang, Jian Feng, Shanyuan Wang
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Statistical Properties of Convex Clustering
, 2015 In this manuscript, we study the statistical properties of convex clustering. We establish that convex clustering is closely related to single linkage hierarchical clustering and $k$-means clustering.
Tan, Kean Ming, Witten, Daniela
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Simple Measures of Individual Cluster-Membership Certainty for Hard Partitional Clustering
, 2018 We propose two probability-like measures of individual cluster-membership certainty which can be applied to a hard partition of the sample such as that obtained from the Partitioning Around Medoids (PAM) algorithm, hierarchical clustering or k-means ...
Graham, Jinko, Liu, Dongmeng
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Random Fuzzy Clustering Granular Hyperplane Classifier
IEEE Access, 2020 Granular computing is a method of studying human intelligent information processing, which has advantage of knowledge discovery. In this paper, we convert a classification problem of sample space into a classification problem of fuzzy clustering granular
Wei Li +5 more
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Active Informative Pairwise Constraint Formulation Algorithm for Constraint-Based Clustering
IEEE Access, 2019 Constraint-based clustering utilizes pairwise constraints to improve clustering performance. In this paper, we propose a novel formulation algorithm to generate more informative pairwise constraints from limited queries for the constraint-based ...
Guoxiang Zhong +2 more
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