Density peak clustering algorithms: A review on the decade 2014–2023
Density peak clustering (DPC) algorithm has become a well-known clustering method
during the last decade, The research communities believe that DPC is a powerful tool …
during the last decade, The research communities believe that DPC is a powerful tool …
Density peaks clustering algorithm based on fuzzy and weighted shared neighbor for uneven density datasets
Uneven density data refers to data with a certain difference in sample density between
clusters. The local density of density peaks clustering algorithm (DPC) does not consider the …
clusters. The local density of density peaks clustering algorithm (DPC) does not consider the …
[HTML][HTML] Enhancing sparrow search algorithm via multi-strategies for continuous optimization problems
J Ma, Z Hao, W Sun - Information Processing & Management, 2022 - Elsevier
As a recent swarm intelligence optimization algorithm, sparrow search algorithm (SSA) is
widely adopted in many real-world problems. However, the solutions to the limitations of …
widely adopted in many real-world problems. However, the solutions to the limitations of …
A sampling-based density peaks clustering algorithm for large-scale data
With the rapid development of information technology, massive amount of data is generated.
How to discover useful information to support decision-making has become one of the …
How to discover useful information to support decision-making has become one of the …
Clustering by fast detection of main density peaks within a peak digraph
J Guan, S Li, X He, J Chen - Information Sciences, 2023 - Elsevier
Abstract The well-known Density Peak Clustering algorithm (DPC) proposed a heuristic
center detection idea, ie, to find density peaks as cluster centers. Nevertheless, such a …
center detection idea, ie, to find density peaks as cluster centers. Nevertheless, such a …
DM-CNN: Dynamic Multi-scale Convolutional Neural Network with uncertainty quantification for medical image classification
Q Han, X Qian, H Xu, K Wu, L Meng, Z Qiu… - Computers in Biology …, 2024 - Elsevier
Convolutional neural network (CNN) has promoted the development of diagnosis
technology of medical images. However, the performance of CNN is limited by insufficient …
technology of medical images. However, the performance of CNN is limited by insufficient …
DCSNE: Density-based clustering using graph shared neighbors and entropy
Density-based clustering techniques identify arbitrary shaped clusters in the presence of
outliers by capturing the intrinsic distribution of data and separating high and low-density …
outliers by capturing the intrinsic distribution of data and separating high and low-density …
SFKNN-DPC: Standard deviation weighted distance based density peak clustering algorithm
J **e, X Liu, M Wang - Information Sciences, 2024 - Elsevier
DPC (Clustering by fast search and find of Density Peaks) algorithm and its variations
typically employ Euclidean distance, overlooking the diverse contributions of individual …
typically employ Euclidean distance, overlooking the diverse contributions of individual …
VDPC: Variational density peak clustering algorithm
The widely applied density peak clustering (DPC) algorithm makes an intuitive cluster
formation assumption that cluster centers are often surrounded by data points with lower …
formation assumption that cluster centers are often surrounded by data points with lower …
A fast spectral clustering technique using MST based proximity graph for diversified datasets
Spectral clustering is a popular unsupervised learning technique used for exploratory
analysis of complex datasets. In spectral clustering, the efficient construction of a sparse …
analysis of complex datasets. In spectral clustering, the efficient construction of a sparse …