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Enhancing and Combining a Recent K-means Family of Algorithms

 

Marketed By :  LAP LAMBERT Academic Publishing   Sold By :  Kamal Books International  
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  • Product Description
 

Clustering is widely used to explore and understand large collections of data. K-means clustering method is one of the most popular approaches due to its ease of use and simplicity to implement. In this book, the researcher introduces Distance-based Initialization Method for K-means clustering algorithm (DIMK-means) which is developed to select carefully a set of centroids that would get high accuracy results compared to the random selection of standard K-means clustering method in choosing initial centroids, which gets low accuracy results. The researcher also Introduces Density-based Split- and -Merge K-means clustering Algorithm (DSMK-means) which is developed to address stability problems of K-means clustering, and to improve the performance of clustering when dealing with datasets that contain clusters with different complex shapes and noise or outliers. Based on a set of many experiments, this research concluded that the developed algorithms are more capable to finding high accuracy results compared with other algorithms.

Product Specifications
SKU :COC65488
AuthorRaed Aldahdooh and Wesam Ashour
LanguageEnglish
BindingPaperback
Number of Pages120
Publishing Year2013-08-30T00:00:00.000
ISBN9783659447952
Edition1 st
Book TypeComputing & information technology
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-07-08 00:00:00
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