Results 31 to 40 of about 1,195,838 (307)
Journal of King Saud University: Computer and Information Sciences, 2023 Recently, both ensemble clustering and semi-supervised clustering have emerged as important paradigms of traditional clustering. Ensemble clustering seeks to integrate multiple clustering results from different methods or the same methods with different ...
Hui Shi +3 more
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Direct reading algorithm for hierarchical clustering [PDF]
, 2016 Reading the clusters from a data set such that the overall computational complexity is linear in both data dimensionality and in the number of data elements has been carried out through filtering the data in wavelet transform space.
Murtagh, Fionn, Contreras, Pedro
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Convex clustering: an attractive alternative to hierarchical clustering.
PLoS Computational Biology, 2015 The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims.
Gary K Chen +3 more
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A Fast Quad-Tree Based Two Dimensional Hierarchical Clustering
Bioinformatics and Biology Insights, 2012 Recently, microarray technologies have become a robust technique in the area of genomics. An important step in the analysis of gene expression data is the identification of groups of genes disclosing analogous expression patterns.
Priscilla Rajadurai +1 more
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Bioengineering, 2022 Heart failure with preserved ejection (HFpEF) is a heterogenous condition affecting nearly half of all patients with heart failure (HF). Artificial intelligence methodologies can be useful to identify patient subclassifications with important clinical ...
Hirmand Nouraei +2 more
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Belief Hierarchical Clustering [PDF]
, 2014 In the data mining field many clustering methods have been proposed, yet standard versions do not take into account uncertain databases. This paper deals with a new approach to cluster uncertain data by using a hierarchical clustering defined within the belief function framework.
Wiem Maalel +3 more
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RECURSIVE HIERARCHICAL CLUSTERING FOR HYPERSPECTRAL IMAGES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Partition based clustering techniques are widely used in data mining and also to analyze hyperspectral images. Unsupervised clustering only depends on data, without any external knowledge.
S. May
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Prioritizing the risk of plant pests by clustering methods : self-organising maps, k-means and hierarchical clustering [PDF]
, 2013 For greater preparedness, pest risk assessors are required to prioritise long lists of pest species with potential to establish and cause significant impact in an endangered area. Such prioritization is often qualitative, subjective, and sometimes biased,
Paini,Dean +26 more
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Bayesian hierarchical clustering for microarray time series data with replicates and outlier measurements [PDF]
, 2011 Background Post-genomic molecular biology has resulted in an explosion of data, providing measurements for large numbers of genes, proteins and metabolites.
Cooke Emma J +14 more
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Neutrosophic Hierarchical Clustering Algoritms [PDF]
Neutrosophic Sets and Systems, 2014 Interval neutrosophic set (INS) is a generalization of interval valued intuitionistic fuzzy set (IVIFS), whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS) is regarded as ...
Rıdvan Şahin
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