Výsledky vyhledávání - Data Clustering Techniques and Algorithms

Clustering public hospitals based on crisp and fuzzy clustering techniques and probabilistic fuzzy efficiency estimates.

Autoři: Cinaroglu, Songul¹ (AUTHOR) scinaroglu@mgh.harvard.edu

Zdroj: Informatics for Health & Social Care. 2025, Vol. 50 Issue 3/4, p114-132. 19p.

Témata: *Data envelopment analysis, Fuzzy clustering technique, Public hospitals, Fuzzy algorithms, K-means clustering, Clustering algorithms, Mechanical efficiency, Self-organizing maps

On Simulating Skewed and Cluster-Weighted Data for Studying Performance of Clustering Algorithms

Autoři: Volodymyr Melnykov Yan Wang Yana Melnykov a další

Zdroj: Journal of Computational and Graphical Statistics. 33:303-309

Témata: Data Clustering Techniques and Algorithms, Algorithm, Artificial intelligence, Cluster analysis, Artificial Intelligence, 4. Education, Computer Science, Physical Sciences, Cluster (spacecraft), Computer science, Data mining, Programming language

Data Clustering using Two-Stage Eagle Strategy Based on Slime Mould Algorithm

Autoři: Rachid Oucheikh Achraf Touil Mouhsene Fri

Zdroj: Journal of Computer Science. 18:1062-1084

Témata: Data Clustering Techniques and Algorithms, Artificial intelligence, 4. Education, Mathematical optimization, Metaheuristic, 02 engineering and technology, 15. Life on land, Semi-supervised Clustering, Computer science, 7. Clean energy, Algorithm, Clustering Algorithms, Fuzzy Clustering, Cluster analysis, Artificial Intelligence, Document Clustering, Computer Science, Physical Sciences, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Swarm Intelligence Optimization Algorithms, Stream Data Clustering, Mathematics

A systematic review of symbiotic organisms search algorithm for data clustering and predictive analysis

Autoři: Abbas Fadhil Jasim AL-Gburi Mohd Zakree Ahmad Nazri Mohd Ridzwan Yaakub a další

Zdroj: Journal of Intelligent Systems, Vol 33, Iss 1, Pp 169-85 (2024)

Témata: Artificial intelligence, Science, 02 engineering and technology, Clustering Algorithms, feature selection, Cluster analysis, systematic review, symbiotic organisms search algorithm, Artificial Intelligence, Document Clustering, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, 14. Life underwater, Adaptation to Concept Drift in Data Streams, Data mining, Adaptive Algorithms, Data Clustering Techniques and Algorithms, QA75.5-76.95, 15. Life on land, Semi-supervised Clustering, Computer science, Algorithm, Informatik, Sonstiges, classification, Electronic computers. Computer science, Computer Science, Physical Sciences, Density-based Clustering, clustering

Popis souboru: image/jpeg; application/pdf

Přístupová URL adresa: https://doaj.org/article/25a0db704b474652bb2ed0311a8ffb4e

A Novel Classification Algorithm Based on the Synergy Between Dynamic Clustering with Adaptive Distances and K-Nearest Neighbors

Autoři: Sabri, Mohammed Verde, Rosanna Balzanella, Antonio a další

Zdroj: Journal of Classification. 41:264-288

Témata: Artificial intelligence, 02 engineering and technology, Pattern recognition (psychology), 7. Clean energy, Clustering Algorithms, Cluster analysis, Artificial Intelligence, Document Clustering, Multi-label Text Classification in Machine Learning, 0202 electrical engineering, electronic engineering, information engineering, FOS: Mathematics, Canopy clustering algorithm, Data mining, Data Clustering Techniques and Algorithms, Spectral Clustering, 4. Education, Correlation clustering, 15. Life on land, k-means clustering, Semi-supervised Clustering, Computer science, Nearest-neighbor chain algorithm, Algorithm, Computer Science, Physical Sciences, Computer Vision and Pattern Recognition, k-nearest neighbors algorithm, Face Recognition and Dimensionality Reduction Techniques, Density-based Clustering, Mathematics

Morphological Accuracy Data Clustering: A Novel Algorithm for Enhanced Cluster Analysis

Autoři: A. A. Azzam ahmed maghrabi Eman El-Naqeeb a další

Zdroj: Applied Computational Intelligence and Soft Computing, Vol 2024 (2024)

Témata: Artificial intelligence, 02 engineering and technology, Cluster (spacecraft), Pattern recognition (psychology), 01 natural sciences, Clustering Algorithms, Cluster analysis, Artificial Intelligence, Document Clustering, Shape Matching and Object Recognition, 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics, Data mining, Data Clustering Techniques and Algorithms, Spectral Clustering, 4. Education, QA75.5-76.95, 15. Life on land, 16. Peace & justice, Semi-supervised Clustering, Computer science, Algorithm, Operating system, Electronic computers. Computer science, Computer Science, Physical Sciences, Computer Vision and Pattern Recognition, Face Recognition and Dimensionality Reduction Techniques, Density-based Clustering

Přístupová URL adresa: https://doaj.org/article/88ef3ae4aba246dfa3be88909a82ff16

Geometry-Inference based Clustering Heuristic: A New kmeans initialization technique for Gaussian data and Experimental Proof of concept

Autoři: Mohammed-Zakariae El Khattabi Mostapha El Jai Youssef Lahmadi a další

Témata: Artificial intelligence, Trajectory Data Mining and Analysis, Heuristic, Pattern recognition (psychology), Quantum mechanics, Clustering, Clustering Algorithms, Cluster analysis, Artificial Intelligence, FOS: Mathematics, Initialization, Data Clustering Techniques and Algorithms, Geography, Physics, 4. Education, k-means clustering, Semi-supervised Clustering, Computer science, Programming language, Algorithm, Computer Science, Physical Sciences, Signal Processing, Gaussian, Benchmark (surveying), Model-Based Clustering with Mixture Models, Stream Data Clustering, Density-based Clustering, Mathematics, Geodesy

Clustering Analysis of Multivariate Data: A Weighted Spatial Ranks-Based Approach

Autoři: Mohammed Baragilly Hend Gabr Brian H Willis

Zdroj: Journal of Probability and Statistics, Vol 2023 (2023)

Témata: Sensory Analysis in Food Science Research, Artificial intelligence, Cluster (spacecraft), 02 engineering and technology, Pattern recognition (psychology), Quantum mechanics, 01 natural sciences, QA273-280, Clustering, Agricultural and Biological Sciences, Clustering Algorithms, Cluster analysis, Artificial Intelligence, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, 0101 mathematics, Data mining, Data Clustering Techniques and Algorithms, Nonparametric statistics, Physics, Statistics, Spatial analysis, Life Sciences, Measure (data warehouse), Semi-supervised Clustering, Computer science, Multivariate statistics, Programming language, Rank (graph theory), Combinatorics, Computer Science, Physical Sciences, Gaussian, Kernel (algebra), Model-Based Clustering with Mixture Models, Stream Data Clustering, Probabilities. Mathematical statistics, Density-based Clustering, Mathematics, Food Science

Popis souboru: text/xhtml

Přístupová URL adresa: https://doaj.org/article/681bdaf8118f479b92e00a56250e988a

Distributed fuzzy clustering algorithm for mixed-mode data in Apache SPARK

Autoři: Abdul Wahab Akram Zareen Alamgir

Zdroj: Journal of Big Data, Vol 9, Iss 1, Pp 1-18 (2022)

Témata: Computer engineering. Computer hardware, Cluster Validation, Artificial intelligence, Information technology, 02 engineering and technology, 7. Clean energy, TK7885-7895, Anomaly Detection in High-Dimensional Data, Database, Big data, Fuzzy Clustering, Cluster analysis, Artificial Intelligence, Document Clustering, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Data mining, Data Clustering Techniques and Algorithms, Fuzzy clustering, Scalability, Statistical and Nonlinear Physics, QA75.5-76.95, T58.5-58.64, Semi-supervised Clustering, Computer science, Programming language, Fuzzy logic, Algorithm, Physics and Astronomy, Electronic computers. Computer science, Computer Science, Physical Sciences, Statistical Mechanics of Complex Networks, SPARK (programming language), Stream Data Clustering

Přístupová URL adresa: https://doaj.org/article/7d2331da58fb4dcba9903eea16fd849f

The Computational Complexity of Hierarchical Clustering Algorithms for Community Detection: A Review

Autoři: Van Hieu Bui Huyen Trang Phan

Zdroj: Vietnam Journal of Computer Science, Vol 10, Iss 04, Pp 409-431 (2023)

Témata: Cluster Validation, Artificial intelligence, Social Sciences, Experimental and Cognitive Psychology, Information technology, 02 engineering and technology, 7. Clean energy, Hierarchical clustering, Data science, 12. Responsible consumption, Clustering Algorithms, Cluster analysis, Artificial Intelligence, Document Clustering, Field (mathematics), Machine learning, 11. Sustainability, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Network Analysis of Psychopathology and Mental Disorders, Psychology, Community Structure, Data mining, modularity, Data Clustering Techniques and Algorithms, Computational intelligence, Community detection, Pure mathematics, random walks, Statistical and Nonlinear Physics, QA75.5-76.95, T58.5-58.64, Computer science, FOS: Psychology, Computational complexity theory, Algorithm, Physics and Astronomy, networks, Electronic computers. Computer science, Physical Sciences, Computer Science, 8. Economic growth, Statistical Mechanics of Complex Networks, Laplacian, Density-based Clustering, Mathematics

Přístupová URL adresa: https://doaj.org/article/b721308f8e25405593a9c1fcc51cfabd

Clustering objects for spatial data mining: a comparative study

Autoři: Youssef Fakir Rachid Elayachi Btissam MAHI

Zdroj: Journal of Big Data Research. 1:1-11

Témata: FOS: Computer and information sciences, Artificial intelligence, Trajectory Data Mining and Analysis, 7. Clean energy, Clustering Algorithms, Cluster analysis, Artificial Intelligence, Data Mining Techniques and Applications, Document Clustering, 11. Sustainability, FOS: Mathematics, CURE data clustering algorithm, Data mining, Medoid, Data Clustering Techniques and Algorithms, 4. Education, Statistics, Spatial analysis, Correlation clustering, 15. Life on land, Semi-supervised Clustering, Computer science, Computer Science, Physical Sciences, Signal Processing, Object (grammar), Stream Data Clustering, Density-based Clustering, Mathematics, Information Systems, Spatial database

Comparison of K-Means and K-Medoids Algorithms for Clustering Poverty Data in South Sumatra Using DBI Evaluation

Autoři: M. Dandi Akhda Ken Ditha Tania

Zdroj: Digital Zone: Jurnal Teknologi Informasi dan Komunikasi, Vol 15, Iss 2, Pp 233-245 (2024)

Témata: davies bouldin index (dbi), TK7885-7895, Computer engineering. Computer hardware, k-medoids, k-means, Telecommunication, poverty data, TK5101-6720, clustering

Přístupová URL adresa: https://doaj.org/article/7534a7c574f744278a755999356f1108

Optimizing Data Exploration: Unifying Clustering and Association Rule Extraction

Autoři: Youssef Fakir

Témata: FOS: Computer and information sciences, Rough Sets Theory and Applications, Artificial intelligence, Decision Analysis, MEDLINE, FOS: Political science, Data extraction, FOS: Law, Clustering Algorithms, Fuzzy Clustering, Cluster analysis, Context (archaeology), Knowledge extraction, Artificial Intelligence, Data Mining Techniques and Applications, Document Clustering, Machine learning, CURE data clustering algorithm, Data mining, Political science, Data Clustering Techniques and Algorithms, Association rule learning, Geography, Correlation clustering, Computer science, Computational Theory and Mathematics, Archaeology, Computer Science, Physical Sciences, Relevance (law), Consensus clustering, Stream Data Clustering, Law, Information Systems

A Systematic Review of Density Grid-Based Clustering for Data Streams

Autoři: Mustafa Tareq Elankovan A Sundararajan Aaron Harwood a další

Zdroj: IEEE Access, Vol 10, Pp 579-596 (2022)

Témata: Data stream clustering, Geometry, 02 engineering and technology, Clustering of Time Series Data and Algorithms, Clustering, Cluster analysis, Artificial Intelligence, Data Streams, Document Clustering, Machine learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, CURE data clustering algorithm, Grid, data stream, Adaptation to Concept Drift in Data Streams, Data mining, density-based clustering, Data Clustering Techniques and Algorithms, grid-based clustering, Correlation clustering, Data stream mining, data stream clustering, Computer science, TK1-9971, Computer Science, Physical Sciences, Signal Processing, Electrical engineering. Electronics. Nuclear engineering, Stream Data Clustering, Density-based Clustering, Mathematics

Přístupová URL adresa: https://doaj.org/article/8de2244d65d14a5cabde1c667c334bc2

The effective BRKGA algorithm for the k-medoids clustering problem

Autoři: José André de Moura Brito Gustavo Silva Semaan Augusto Fadel

Zdroj: RAIRO - Operations Research. 56:3137-3153

Témata: Vehicle Routing Problem and Variants, Cluster Validation, Artificial intelligence, Hybrid Algorithms, Trajectory Data Mining and Analysis, 0211 other engineering and technologies, Heuristic, 02 engineering and technology, 7. Clean energy, Industrial and Manufacturing Engineering, Clustering Algorithms, Engineering, Cluster analysis, k-medoids, Artificial Intelligence, Computer security, Machine learning, FOS: Mathematics, Stability (learning theory), Key (lock), Canopy clustering algorithm, Medoid, Data Clustering Techniques and Algorithms, Mathematical optimization, Correlation clustering, Integer programming, Semi-supervised Clustering, Computer science, Silhouette, Programming language, Algorithm, Computer Science, Physical Sciences, Signal Processing, Integer (computer science), Density-based Clustering, Mathematics

Clustering functional data using forward search based on functional spatial ranks with medical applications

Autoři: Mohammed Baragilly Hend Gabr Brian H Willis

Zdroj: Stat Methods Med Res

Témata: Statistics and Probability, Artificial intelligence, Regularization and Variable Selection Methods, Pattern recognition (psychology), 01 natural sciences, Clustering, Fuzzy Clustering, Cluster analysis, Artificial Intelligence, Document Clustering, Machine learning, FOS: Mathematics, Cluster Analysis, 0101 mathematics, Data mining, Preprocessor, Data Clustering Techniques and Algorithms, Functional principal component analysis, Articles, Semi-supervised Clustering, Computer science, Dimensionality reduction, Functional data analysis, Rank (graph theory), Combinatorics, Computer Science, Physical Sciences, Clustering high-dimensional data, Model-Based Clustering with Mixture Models, Algorithms, Mathematics, Density-based Clustering

Přístupová URL adresa: https://journals.sagepub.com/doi/pdf/10.1177/09622802211002865
https://pubmed.ncbi.nlm.nih.gov/34756132
https://europepmc.org/article/MED/34756132
https://research.birmingham.ac.uk/en/publications/clustering-functional-data-using-forward-search-based-on-function
https://journals.sagepub.com/doi/full/10.1177/09622802211002865

Clustering and Geodesic Scaling of Dissimilarities on the Spherical Surface

Autoři: José Ramón Navarro Vera Ricardo Subiabre Rodrigo Macías

Zdroj: Digibug. Repositorio Institucional de la Universidad de Granada
Universidad de Granada (UGR)

Témata: Geometry, 01 natural sciences, Scaling, Fuzzy Clustering, Cluster analysis, Artificial Intelligence, Document Clustering, Shape Matching and Object Recognition, FOS: Mathematics, 14. Life underwater, 0101 mathematics, 0105 earth and related environmental sciences, Data Clustering Techniques and Algorithms, Geodesic distance, Physics, Statistics, Geometric Morphometrics and Statistical Analysis, 15. Life on land, Semi-supervised Clustering, Computer science, Geodesic, Dissimilarity, 13. Climate action, Physical Sciences, Computer Science, Geometry and Topology, Computer Vision and Pattern Recognition, Surface (topology), Statistical physics, High-Dimensional Data, Mathematics, Density-based Clustering, Multidimensional scaling

Přístupová URL adresa: https://hdl.handle.net/10481/91493

An ensemble clustering approach for modeling hidden categorization perspectives for cloud workloads

Autoři: Mustafa Daraghmeh Anjali Agarwal Yaser Jararweh

Zdroj: Cluster Computing. 27:4779-4803

Témata: FOS: Computer and information sciences, Artificial intelligence, Environmental Engineering, 02 engineering and technology, Workload, Cloud Computing and Big Data Technologies, Bottleneck, Low-Cost Air Quality Monitoring Systems, Clustering Algorithms, Cluster analysis, Artificial Intelligence, Document Clustering, Machine learning, 0202 electrical engineering, electronic engineering, information engineering, Cloud computing, Embedded system, Data mining, Data Clustering Techniques and Algorithms, FOS: Environmental engineering, Cloud Computing, Semi-supervised Clustering, Computer science, Operating system, Categorization, Computer Science, Physical Sciences, Environmental Science, Stream Data Clustering, Information Systems

An Automatic Merge Technique to Improve the Clustering Quality Performed by LAMDA

Autoři: Morales, Luis Aguilar, Jose Universidad EAFIT. Departamento de Ingeniería de Sistemas a další

Přispěvatelé: Morales, Luis Aguilar, Jose Universidad EAFIT. Departamento de Ingeniería de Sistemas a další

Zdroj: IEEE Access, Vol 8, Pp 162917-162944 (2020)
IEEE Access

Témata: Cluster Validation, Artificial intelligence, Clustering algorithms, Data analysis, 02 engineering and technology, unsupervised learning, Unsupervised learning, Anomaly Detection in High-Dimensional Data, Fuzzy Clustering, Cluster analysis, Artificial Intelligence, Document Clustering, Machine learning, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, Proposals, Information retrieval, Adaptation to Concept Drift in Data Streams, Data mining, Data Clustering Techniques and Algorithms, Benchmark testing, Fuzzy clustering, Production, Automatic merging, Partition (number theory), Semi-supervised Clustering, Computer science, Partitioning algorithms, TK1-9971, Fuzzy logic, Combinatorics, Computer Science, Physical Sciences, LAMDA, Merge (version control), Electrical engineering. Electronics. Nuclear engineering, Stream Data Clustering, Mathematics, clustering

Popis souboru: application/pdf

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09186029.pdf
https://doaj.org/article/8a24d48c6ab04e9a9a1cb635ec22f427
https://dblp.uni-trier.de/db/journals/access/access8.html#MoralesA20
https://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=12241
http://hdl.handle.net/10784/28656

Applying Clustering Techniques and Geostatistics to the Definition of Domains for Modelling

Autoři: Gabriel de Castro Moreira João Felipe Coimbra Leite Costa Diego Machado Marques

Zdroj: Springer Proceedings in Earth and Environmental Sciences ISBN: 9783031198441

Témata: Artificial intelligence, Environmental Engineering, Resource (disambiguation), Digital Soil Mapping Techniques, 7. Clean energy, Workflow, Database, Clustering Algorithms, Cluster analysis, Artificial Intelligence, Terrain Analysis, Document Clustering, Field (mathematics), Machine learning, Machine Learning for Mineral Prospectivity Mapping, FOS: Mathematics, 14. Life underwater, Data mining, Data Clustering Techniques and Algorithms, Computer network, FOS: Environmental engineering, Pure mathematics, 15. Life on land, Semi-supervised Clustering, Computer science, Process (computing), Operating system, Computer Science, Physical Sciences, Environmental Science, Density-based Clustering, Mathematics