Results 21 to 30 of about 3,381,889 (354)
Analysis of whole-brain resting-state FMRI data using hierarchical clustering approach. [PDF]
PLoS ONE, 2013 BACKGROUND: Previous studies using hierarchical clustering approach to analyze resting-state fMRI data were limited to a few slices or regions-of-interest (ROIs) after substantial data reduction.
Yanlu Wang, Tie-Qiang Li
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Applied Sciences, 2021 With the frequent occurrence of network security events, the intrusion detection system will generate alarm and log records when monitoring the network environment in which a large number of log and alarm records are redundant, which brings great burden ...
Leiting Wang, Lize Gu, Yifan Tang
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Hierarchical Clustering: A Survey
International Journal of Applied Research, 2021 There is a need to scrutinise and retrieve information from data in today's world. Clustering is an analytical technique which involves dividing data into groups of similar objects. Every group is called a cluster, and it is formed from objects that have
Pranav Shetty, Suraj Singh
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Clustering Acoustic Segments Using Multi-Stage Agglomerative Hierarchical Clustering. [PDF]
PLoS ONE, 2015 Agglomerative hierarchical clustering becomes infeasible when applied to large datasets due to its O(N2) storage requirements. We present a multi-stage agglomerative hierarchical clustering (MAHC) approach aimed at large datasets of speech segments.
Lerato Lerato, Thomas Niesler
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IEEE Access, 2022 Adaptive Resonance Theory (ART) is considered as an effective approach for realizing continual learning thanks to its ability to handle the plasticity-stability dilemma.
Naoki Masuyama +4 more
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Interactive Steering of Hierarchical Clustering [PDF]
IEEE Transactions on Visualization and Computer Graphics, 2020 Hierarchical clustering is an important technique to organize big data for exploratory data analysis. However, existing one-size-fits-all hierarchical clustering methods often fail to meet the diverse needs of different users.
Weikai Yang +4 more
semanticscholar +1 more source
Relation between financial market structure and the real economy: comparison between clustering methods. [PDF]
PLoS ONE, 2015 We quantify the amount of information filtered by different hierarchical clustering methods on correlations between stock returns comparing the clustering structure with the underlying industrial activity classification.
Nicoló Musmeci +2 more
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Robust hierarchical k-center clustering [PDF]
, 2015 One of the most popular and widely used methods for data clustering is hierarchical clustering. This clustering technique has proved useful to reveal interesting structure in the data in several applications ranging from computational biology to computer
Lattanzi, Silvio +3 more
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Multi-attribute Hierarchical Clustering for Product Family Division of Customized Wooden Doors
BioResources, 2023 To improve the production system for customized wooden doors and to gain research and development efficiency, this paper proposed the feasibility of using hierarchical clustering algorithms to cluster a company's customized wooden door products and its ...
Na Zhang, Wei Xu, Yong Tan
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HIERARCHICAL SPHERICAL CLUSTERING
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2002 This work introduces an alternative representation for large dimensional data sets. Instead of using 2D or 3D representations, data is located on the surface of a sphere. Together with this representation, a hierarchical clustering algorithm is defined to analyse and extract the structure of the data.
Torra, Vincenç, Miyamoto, Sadaaki
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