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Early Classification: A New Heuristic to Improve the Classification Step of K-Means

Autor: Pérez, Joaquín, Pires, Carlos Eduardo, Balby, Leandro, Mexicano, Adriana, Hidalgo, Miguel Ángel

Publikováno v: Journal of Information and Data Management; v. 4, n. 2 (2013): JOURNAL OF INFORMATION AND DATA MANAGEMENT; 94
Journal of Information and Data Management; Vol 4 No 2 (2013): JOURNAL OF INFORMATION AND DATA MANAGEMENT; 94
Journal of Information and Data Management; v. 4 n. 2 (2013): JOURNAL OF INFORMATION AND DATA MANAGEMENT; 94

Cluster analysis is the study of algorithms and techniques for grouping objects according to their intrinsic characteristics and similarity. A widely studied and popular clustering algorithm is K-Means, which is characterized by its ease of implement

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::48df95a1ba4a20f4f0f5bf78e54ad948
https://seer.ufmg.br/index.php/jidm/article/view/218

Adaptive Threshold and Principal Component Analysis for Features Extraction of Electrocardiogram Signals.

Autor: Rodriguez, Ricardo, Mexicano, Adriana, Bila, Jiri, Ponce, Rafael, Cervantes, Salvador

Publikováno v: 2014 International Symposium on Computer, Consumer & Control; 2014, p1253-1258, 6p

Extracting the QRS Complexity and R Beats in Electrocardiogram Signals Using the Hilbert Transform.

Autor: Rodríguez, Ricardo, Mexicano, Adriana, Cervantes, Salvador, Bila, Jiri, Ponce, Rafael

Publikováno v: ISCS 2013: Interdisciplinary Symposium on Complex Systems; 2014, p203-213, 11p