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 - Books - LAP LAMBERT Academic Publishing - 9783659140259 - June 16, 2012
In case cover and title do not match, the title is correct

An Improved Dbscan Algorithm for High Dimensional Datasets: an Improvement in Terms of Number of Clusters an in General Increasing the Accuracy of Algorithm


Get an email once the item is available
Do you have a profile? Log in
Get notified about new Glory Shah releases
Add to your iMusic wish list

Not rated yet

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.

Media Books     Paperback Book   (Book with soft cover and glued back)
Released June 16, 2012
ISBN13 9783659140259
Publishers LAP LAMBERT Academic Publishing
Pages 140
Dimensions 150 × 8 × 226 mm   ·   213 g
Language English