PKK Library

Your cart is empty.

Welcome to P K Kelkar Library, Online Public Access Catalogue (OPAC)

Normal view MARC view ISBD view

Evolutionary Computation in Data Mining

Contributor(s): Ghosh, Ashish [editor.] | Jain, Lakhmi C [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Fuzziness and Soft Computing: 163Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.Description: XVIII, 266 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540323587.Subject(s): Computer science | Database management | Artificial intelligence | Applied mathematics | Engineering mathematics | Computer Science | Artificial Intelligence (incl. Robotics) | Appl.Mathematics/Computational Methods of Engineering | Database ManagementDDC classification: 006.3 Online resources: Click here to access online
Contents:
Evolutionary Algorithms for Data Mining and Knowledge Discovery -- Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining -- GAP: Constructing and Selecting Features with Evolutionary Computing -- Multi-Agent Data Mining using Evolutionary Computing -- A Rule Extraction System with Class-Dependent Features -- Knowledge Discovery in Data Mining via an Evolutionary Algorithm -- Diversity and Neuro-Ensemble -- Unsupervised Niche Clustering: Discovering an Unknown Number of Clusters in Noisy Data Sets -- Evolutionary Computation in Intelligent Network Management -- Genetic Programming in Data Mining for Drug Discovery -- Microarray Data Mining with Evolutionary Computation -- An Evolutionary Modularized Data Mining Mechanism for Financial Distress Forecasts.
In: Springer eBooksSummary: This carefully edited book reflects and advances the state of the art in the area of Data Mining and Knowledge Discovery with Evolutionary Algorithms. It emphasizes the utility of different evolutionary computing tools to various facets of knowledge discovery from databases, ranging from theoretical analysis to real-life applications. "Evolutionary Computation in Data Mining" provides a balanced mixture of theory, algorithms and applications in a cohesive manner, and demonstrates how the different tools of evolutionary computation can be used for solving real-life problems in data mining and bioinformatics.
    average rating: 0.0 (0 votes)
Item type Current location Call number Status Date due Barcode Item holds
E books E books PK Kelkar Library, IIT Kanpur
Available EBK7631
Total holds: 0

Evolutionary Algorithms for Data Mining and Knowledge Discovery -- Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining -- GAP: Constructing and Selecting Features with Evolutionary Computing -- Multi-Agent Data Mining using Evolutionary Computing -- A Rule Extraction System with Class-Dependent Features -- Knowledge Discovery in Data Mining via an Evolutionary Algorithm -- Diversity and Neuro-Ensemble -- Unsupervised Niche Clustering: Discovering an Unknown Number of Clusters in Noisy Data Sets -- Evolutionary Computation in Intelligent Network Management -- Genetic Programming in Data Mining for Drug Discovery -- Microarray Data Mining with Evolutionary Computation -- An Evolutionary Modularized Data Mining Mechanism for Financial Distress Forecasts.

This carefully edited book reflects and advances the state of the art in the area of Data Mining and Knowledge Discovery with Evolutionary Algorithms. It emphasizes the utility of different evolutionary computing tools to various facets of knowledge discovery from databases, ranging from theoretical analysis to real-life applications. "Evolutionary Computation in Data Mining" provides a balanced mixture of theory, algorithms and applications in a cohesive manner, and demonstrates how the different tools of evolutionary computation can be used for solving real-life problems in data mining and bioinformatics.

There are no comments for this item.

Log in to your account to post a comment.

Powered by Koha