An Improved Dbscan Algorithm for High Dimensional Datasets: an Improvement in Terms of Number of Clusters an in General Increasing the Accuracy of Algorithm - Glory Shah - Grāmatas - LAP LAMBERT Academic Publishing - 9783659140259 - 2012. gada 16. jūnijs
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An Improved Dbscan Algorithm for High Dimensional Datasets: an Improvement in Terms of Number of Clusters an in General Increasing the Accuracy of Algorithm


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Emergence of modern techniques for scientific data collection has resulted in large scale accumulation of data pertaining to diverse fields. Conventional database querying methods are inadequate to extract useful information from huge data banks. Cluster analysis is one of the major data analysis methods. It is the art of detecting groups of similar objects in large data sets without having specified groups by means of explicit features. The problem of detecting clusters of points is challenging when the clusters are of different size, density and shape. The development of clustering algorithms has received a lot of attention in the last few years and many new clustering algorithms have been proposed. Thus this book provides detailed knowlege regarding density based clustering algorithms and an improvement over one of the algorithm.

Mediji Grāmatas     Paperback Book   (Grāmata ar mīksto vāku un līmēto muguru)
Izlaists 2012. gada 16. jūnijs
ISBN13 9783659140259
Izdevēji LAP LAMBERT Academic Publishing
Lapas 140
Izmēri 150 × 8 × 226 mm   ·   213 g
Valoda Angļu