Výsledky vyhľadávania - "Determining the number of clusters in a data set"
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1
Autori: Adeleke Raheem Ajiboye
Zdroj: International Journal of Software Engineering and Computer Systems. 4:38-48
Predmety: Artificial intelligence, Data stream clustering, Cluster (spacecraft), 02 engineering and technology, Pattern recognition (psychology), Clustering Algorithms, Cluster analysis, Artificial Intelligence, Document Clustering, Shape Matching and Object Recognition, 0202 electrical engineering, electronic engineering, information engineering, Image Compression Techniques and Standards, CURE data clustering algorithm, Canopy clustering algorithm, Data mining, Data Clustering Techniques and Algorithms, Single-linkage clustering, Correlation clustering, Semi-supervised Clustering, Computer science, Programming language, Algorithm, Computer Science, Physical Sciences, Computer Vision and Pattern Recognition, Determining the number of clusters in a data set, Stream Data Clustering, Density-based Clustering
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2
Autori:
Zdroj: Indonesian Journal of Electrical Engineering and Informatics (IJEEI). 5
Predmety: FOS: Computer and information sciences, Artificial intelligence, Population, 02 engineering and technology, Clustering Algorithms, Cluster analysis, Sociology, Artificial Intelligence, Data Mining Techniques and Applications, Document Clustering, Machine learning, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Swarm Intelligence Optimization Algorithms, CURE data clustering algorithm, Canopy clustering algorithm, Adaptation to Concept Drift in Data Streams, Data mining, Demography, Data Clustering Techniques and Algorithms, 05 social sciences, Correlation clustering, Semi-supervised Clustering, Computer science, FOS: Sociology, Algorithm, Genetic algorithm, Computer Science, Physical Sciences, Crossover, Determining the number of clusters in a data set, Stream Data Clustering, Density-based Clustering, Information Systems
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3
Autori: a ďalší
Zdroj: The Proceedings of the 2nd International Conference on Industrial Application Engineering 2015.
Predmety: FOS: Computer and information sciences, Cluster Validation, Artificial intelligence, 02 engineering and technology, Pattern recognition (psychology), Quantum mechanics, 7. Clean energy, Clustering Methods, Cluster analysis, Artificial Intelligence, Data Mining Techniques and Applications, FOS: Mathematics, 0202 electrical engineering, electronic engineering, information engineering, CURE data clustering algorithm, Data mining, Data Clustering Techniques and Algorithms, Mixture model, Single-linkage clustering, Physics, 4. Education, K-Means Clustering, Correlation clustering, Semi-supervised Clustering, Computer science, Silhouette, 13. Climate action, Computer Science, Physical Sciences, Gaussian, Determining the number of clusters in a data set, Data Mining in Various Applications, Stream Data Clustering, Mathematics, Information Systems
Prístupová URL adresa: https://www2.ia-engineers.org/conference/index.php/iciae/iciae2015/paper/download/576/380
https://www2.ia-engineers.org/conference/index.php/iciae/iciae2015/paper/download/576/380
https://jglobal.jst.go.jp/public/201702229911516886
https://www2.ia-engineers.org/conference/index.php/iciae/iciae2015/paper/view/576
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