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Clustering by Constrained Gravitational Law Based on Multiple Sub-Centroids
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Gravitational search algorithm based optimized deep learning model with diverse set of features for facial expression recognition
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GSA for machine learning problems: A comprehensive overview
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An antigravity-based fuzzy Gravitational Search Algorithm for economic dispatch problems
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A review on semi-supervised clustering
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Semi-supervised and un-supervised clustering: A review and experimental evaluation
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A novel self-directed learning framework for cluster ensemble
inferredcites →https://doi.org/10.1016/j.knosys.2017.07.010openalex-extracted
Adaptive density peak clustering based on K-nearest neighbors with aggregating strategy
inferredcites →https://doi.org/10.1016/j.neucom.2017.05.072openalex-extracted
Self-training semi-supervised classification based on density peaks of data
inferredcites →https://doi.org/10.1016/j.neucom.2023.01.043openalex-extracted
PDBI: A partitioning Davies-Bouldin index for clustering evaluation
inferredcites →https://doi.org/10.1016/j.patcog.2018.10.015openalex-extracted
Cumulative attribute space regression for head pose estimation and color constancy
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Threshold optimization for F measure of macro-averaged precision and recall
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Beyond k -Means++: Towards better cluster exploration with geometrical information
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visClust: A visual clustering algorithm based on orthogonal projections
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Deep semi-supervised clustering based on pairwise constraints and sample similarity
inferredcites →https://doi.org/10.1016/j.patrec.2024.01.024openalex-extracted
An analytic study on clustering driven self-supervised speaker verification
inferredcites →https://doi.org/10.1016/j.swevo.2018.02.018openalex-extracted
A comprehensive survey on gravitational search algorithm
inferredcites →https://doi.org/10.1093/hesc/9780198712541.001.0001openalex-extracted
Scientific Data Analysis
inferredcites →https://doi.org/10.1109/iccwamtip47768.2019.9067665openalex-extracted
Rapid Clustering with Semi-Supervised Ensemble Density Centers
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A Binary Linear Programming-Based K-Means Algorithm For Clustering with Must-Link and Cannot-Link Constraints
inferredcites →https://doi.org/10.1109/tkde.2013.22openalex-extracted
Active Learning of Constraints for Semi-Supervised Clustering
inferredcites →https://doi.org/10.1109/tpami.2011.177openalex-extracted
Sparse Algorithms Are Not Stable: A No-Free-Lunch Theorem
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Semi-Supervised Clustering With Constraints of Different Types From Multiple Information Sources
inferredcites →https://doi.org/10.1109/tpami.2022.3188160openalex-extracted
Self-Constrained Spectral Clustering
inferredcites →https://doi.org/10.1111/1740-9713.01589openalex-extracted
The Iris Data Set: In Search of the Source ofVirginica
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A Novel Cluster Ensemble based on a Single Clustering Algorithm
inferredcites →https://doi.org/10.48550/arxiv.1911.02490openalex-extracted
OpenML-Python: an extensible Python API for OpenML
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A k-Means Algorithm for Clustering with Soft Must-link and Cannot-link Constraints
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Comprehensive Differentiation of Partitional Clusterings
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