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Strengthening Links Between Data Analysis and Soft Computing [electronic resource] / edited by Przemyslaw Grzegorzewski, Marek Gagolewski, Olgierd Hryniewicz, Mar�ia �Angeles Gil.

Contributor(s): Grzegorzewski, Przemyslaw [editor.] | Gagolewski, Marek [editor.] | Hryniewicz, Olgierd [editor.] | Gil, Mar�ia �Angeles [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Advances in Intelligent Systems and Computing: 315Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: XII, 294 p. 42 illus., 3 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319107653.Subject(s): Engineering | Artificial intelligence | Computational intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Soft methods in uncertainty modeling and processing -- Soft methods in statistics -- Soft methods in data analysis.
In: Springer eBooksSummary: This book gathers contributions presented at the 7th International Conference on Soft Methods in Probability and Statistics SMPS 2014, held in Warsaw (Poland) on September 22-24, 2014. Its aim is to present recent results illustrating new trends in intelligent data analysis. It gives a comprehensive overview of current research into the fusion of soft computing methods with probability and statistics. Synergies of both fields might improve intelligent data analysis methods in terms of robustness to noise and applicability to larger datasets, while being able to efficiently obtain understandable solutions of real-world problems.
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Soft methods in uncertainty modeling and processing -- Soft methods in statistics -- Soft methods in data analysis.

This book gathers contributions presented at the 7th International Conference on Soft Methods in Probability and Statistics SMPS 2014, held in Warsaw (Poland) on September 22-24, 2014. Its aim is to present recent results illustrating new trends in intelligent data analysis. It gives a comprehensive overview of current research into the fusion of soft computing methods with probability and statistics. Synergies of both fields might improve intelligent data analysis methods in terms of robustness to noise and applicability to larger datasets, while being able to efficiently obtain understandable solutions of real-world problems.

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