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An ensemble method for estimating the number of clusters in a big data set using multiple random samples.

, , , and . J. Big Data, 10 (1): 40 (December 2023)

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Slice_OP: Selecting Initial Cluster Centers Using Observation Points., , , , and . ADMA, volume 11323 of Lecture Notes in Computer Science, page 17-30. Springer, (2018)Variational Autoencoder-Based Dimensionality Reduction for High-Dimensional Small-Sample Data Classification., , and . Int. J. Comput. Intell. Appl., 19 (1): 2050002 (2020)Smart Fire Detection System with Early Notifications Using Machine Learning., , and . Int. J. Comput. Intell. Appl., 16 (2): 1750009:1-1750009:17 (2017)A review of optimization methods for computation offloading in edge computing networks., , , , , and . Digit. Commun. Networks, 9 (2): 450-461 (April 2023)Approximate Clustering Ensemble Method for Big Data., , , , and . IEEE Trans. Big Data, 9 (4): 1142-1155 (August 2023)An ensemble method for estimating the number of clusters in a big data set using multiple random samples., , , and . J. Big Data, 10 (1): 40 (December 2023)Unsupervised classification of high-dimension and low-sample data with variational autoencoder based dimensionality reduction., and . ICARM, page 498-503. IEEE, (2019)High-Dimensional Limited-Sample Biomedical Data Classification Using Variational Autoencoder., , , and . AusDM, volume 996 of Communications in Computer and Information Science, page 30-42. Springer, (2018)Unsupervised Adaptation for High-Dimensional with Limited-Sample Data Classification Using Variational Autoencoder., , , , and . Comput. Informatics, 40 (1): 1-28 (2021)