Machine Learning and Data Mining in Pattern Recognition

Name: Machine Learning and Data Mining in Pattern Recognition
Brand: Petra Perner, Azriel Rosenfeld
SKU: 1222841202
Price: 44.68 EUR
Availability: InStock

Third International Conference, MLDM 2003, Leipzig, Germany, July 5-7, 2003, proceedings

von Petra Perner, Azriel Rosenfeld Verlag: Springer Berlin,

2003 - Erschienen 2003.

Gepflegter, sauberer Zustand. Aus der Auflösung einer renommierten Bibliothek. Kann Stempel beinhalten. 1222841/202

principal component analysis, Fuzzy, classification, autonom, algorithmic learning, statistical learning, algorithms, intelligent data analysis, pattern recognition, Bayesian network, machine learning, Support Vector Machine, LA, decision trees, object recognition,

Produktart:: 📚 Bücher
Autor(en):: Perner, Petra und Azriel Rosenfeld:
Anbieter:: Buchpark GmbH
Bestell-Nr.:: 1222841202
Katalog:: Varia
ISBN | EAN:: 3540405046 | 9783540405047
Stichworte:: principal, component, analysis, Fuzzy, classification, autonom, algorithmic, learning, statistical, algorithms, intelligent, data, pattern, recognition, Bayesian, network, machine, Support, Vector, Machine, decision, trees, object…
Zahlungsarten:: Vorauskasse, PayPal

Gebraucht, sehr gut ~~44,68 EUR~~ 40,21 EUR Kostenloser Versand

Sonderaktion: 10% Rabatt bis 05.11.2026

Verlagstext

TheInternationalConferenceonMachineLearningandDataMining(MLDM)is the third meeting in a series of biennial events, which started in 1999, organized by the Institute of Computer Vision and Applied Computer Sciences (IBaI) in Leipzig. MLDM began as a workshop and is now a conference, and has brought the topic of machine learning and data mining to the attention of the research community. Seventy-?ve papers were submitted to the conference this year. The program committeeworkedhardtoselectthemostprogressiveresearchinafairandc- petent review process which led to the acceptance of 33 papers for presentation at the conference. The 33 papers in these proceedings cover a wide variety of topics related to machine learning and data mining. The two invited talks deal with learning in case-based reasoning and with mining for structural data. The contributed papers can be grouped into nine areas: support vector machines; pattern dis- very; decision trees; clustering; classi?cation and retrieval; case-based reasoning; Bayesian models and methods; association rules; and applications. We would like to express our appreciation to the reviewers for their precise andhighlyprofessionalwork.WearegratefultotheGermanScienceFoundation for its support of the Eastern European researchers. We appreciate the help and understanding of the editorial sta? at Springer Verlag, and in particular Alfred Hofmann,whosupportedthepublicationoftheseproceedingsintheLNAIseries. Last, but not least, we wish to thank all the speakers and participants who contributed to the success of the conference.