K-means Clustering Algorithm: Implementati...

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Sprache: Englisch

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Beschreibung

Clustering is considered as widely used data mining practices. Clustering is the technique of dividing entire dataset in certain clusters created on the comparable characteristics of the instances. On the foundation of the likeness between the instances of data, grouping or clustering the instances of the large database regardless of its size is considered as significant chunk of data mining. There are plentiful approaches of clustering but this book mainly focuses on improving k-Means clustering algorithm. This method clusters the input dataset in quantified number (k) of groups. This method is verified to be very efficient when while dealing with small data, but for huge data, it fails in time complexity; it takes time more than usual. This work mainly aims comparison of k-means clustering scheme with ranking method to speed up the comprehensive running time for k-Means clustering algorithm. The experimental results clearly confirms that the new technique is more time efficient than the old-style k-Means clustering method.

Über den Autor

Swati is a keen researcher in various fields like data mining, internet security, cloud Computing and Image Processing. She holds master's degree in computer engineering from North Maharashtra University, Jalgaon, India with several national and international publications.

Details

Erscheinungsjahr:	2019
Fachbereich:	Nachrichtentechnik
Genre:	Importe , Technik
Rubrik:	Naturwissenschaften & Technik
Medium:	Taschenbuch
Inhalt:	68 S.
ISBN-13:	9786138838197
ISBN-10:	613883819X
Sprache:	Englisch
Einband:	Kartoniert / Broschiert
Autor:	Patel, Swati
Hersteller:	Scholars' Press
Verantwortliche Person für die EU:	preigu GmbH & Co. KG, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de
Maße:	220 x 150 x 5 mm
Von/Mit:	Swati Patel
Erscheinungsdatum:	13.07.2019
Gewicht:	0,119 kg