Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)

Description

pic info: 2007-05-16/EvolutionaryHComputationLinHDataPMiningVStudiesVinOFuzzinessMandLSoftJComputing_orig
Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)
9783540223702 | (3540223703) | Springer | 2004 | 15 MB | RS | FF

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.

Data mining (DM) consists of extracting interesting knowledge from realworld, large & complex data sets; and is the core step of a broader process, called the knowledge discovery from databases (KDD) process. In addition to the DM step, which actually extracts knowledge from data, the KDD process includes several preprocessing (or data preparation) and post-processing (or knowledge refinement) steps. The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge. Ideally, discovered knowledge should be not only accurate, but also comprehensible and interesting to the user. The total process is highly computation intensive.

The idea of automatically discovering knowledge from databases is a very attractive and challenging task, both for academia and for industry. Hence, there has been a growing interest in data mining in several AI-related areas, including evolutionary algorithms (EAs). The main motivation for applying EAs to KDD tasks is that they are robust and adaptive search methods, which perform a global search in the space of candidate solutions (for instance, rules or another form of knowledge representation).

The evolutionary computing community has been publishing KDD-related articles in a relatively scattered manner in conference proceedings/journals dedicated to knowledge discovery and data mining or evolutionary computing. The objective of this volume is to assemble a set of high-quality original contributions that reflect and advance the state-of-the-art in the area of Data Mining and Knowledge Discovery with Evolutionary Algorithms. The book will also emphasize the utility of different evolutionary computing tools to various facets of KDD, ranging from theoretical analysis to real-life applications.

RapidShare

FileFactory

If you like it, BUY IT !!! ID115746 115746 HelpMan 16 May 2007 09:21 Mirror: Download from Depositfiles.com ID:410258 410258 -=Boss=- 16 May 2007 12:08
Thank you!
ID:410382 410382 Drink 16 May 2007 12:12 MIRROR : IceFile.com ID:410393 410393

Disclaimer:
Contents of this page are indexed from the Internet. All actions are under your responsability. Email us to report illegal contents or external links and we'll remove them immediately.

Please check the description for download links if any or do a search to find alternative books.

Can't Download?
Please search mirrors if you can't find download links for "Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)" in "Description" and someone else may update the links. Check the comments when back to find any updates.

Search Mirrors
Maybe some mirror pages will be helpful, search this book at top of this page or click here to find more info.

1. Ebooks list page : 1012
2. Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)
3. Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)
4. Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing)
5. Foundations and Advances in Data Mining (Studies in Fuzziness and Soft Computing)
6. Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems (Studies in Fuzziness and Soft Computing)
7. Knowledge Mining: Proceedings of the NEMIS 2004 Final Conference (Studies in Fuzziness and Soft Computing)
8. Fundamentals of Statistics with Fuzzy Data (Studies in Fuzziness and Soft Computing)
9. Fundamentals of Statistics with Fuzzy Data (Studies in Fuzziness and Soft Computing)
10. Mathematics of Fuzziness - Basic Issues (Studies in Fuzziness and Soft Computing)
11. Intelligent Multimedia Processing with Soft Computing (Studies in Fuzziness and Soft Computing)
12. Soft Computing Applications in Industry (Studies in Fuzziness and Soft Computing)
13. [request_ebook] Soft Computing in Acoustics: Applications of Neural Networks, Fuzzy Logic and Rough Sets to Musical Acoustics (Studies in Fuzziness and Soft Computing, Vol. 31)
14. The Brain: Fuzzy Arithmetic to Quantum Computing (Studies in Fuzziness and Soft Computing)
15. The Brain: Fuzzy Arithmetic to Quantum Computing (Studies in Fuzziness and Soft Computing)
16. Fuzzy Implications (Studies in Fuzziness and Soft Computing)