Carte K-means Clustering Algorithm: Implementation and Critical Analysis Swati Patel

K-means Clustering Algorithm: Implementation and Critical Analysis

Autor: Swati Patel
Limbă: engleză
Legare: Carte broșată
Editura: Scholars' Press
Disponibilitate: În depozitul extern
Expediem în 5-8 zile
220.15 lei
Clustering is considered as widely used data mining practices. Clustering is the technique of dividi...

Informații despre carte

Autor
Limbă
engleză
Legare
Carte - Carte broșată
Publicat
2019
Pagini
68
EAN
9786138838197
ISBN
613883819X
Enbook ID
24105928
Editura
Greutate
119
Dimensiuni
150 x 220 x 4

Descriere completă

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.

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