By Claus Weihs, Gero Szepannek (auth.), Petra Perner (eds.)
This ebook constitutes the refereed court cases of the ninth business convention on facts Mining, ICDM 2009, held in Leipzig, Germany in July 2009.
The 32 revised complete papers offered have been rigorously reviewed and chosen from one hundred thirty submissions. The papers are prepared in topical sections on information mining in drugs and agriculture, information mining in advertising, finance and telecommunication, facts mining in technique keep an eye on, and society, facts mining on multimedia facts and theoretical features of information mining.
Read Online or Download Advances in Data Mining. Applications and Theoretical Aspects: 9th Industrial Conference, ICDM 2009, Leipzig, Germany, July 20 - 22, 2009. Proceedings PDF
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Extra info for Advances in Data Mining. Applications and Theoretical Aspects: 9th Industrial Conference, ICDM 2009, Leipzig, Germany, July 20 - 22, 2009. Proceedings
Furthermore, this article can be seen as a continuation of : in the previous article artificial neural networks have been evaluated and established as a well-suited reference model, which further models would have to compete against. The current work compares this particular neural network model with suitable further techniques (such as regression trees or support vector machines) to find the best prediction model. To accomplish this, the model output on site-year data from different years and sites is compared.
That it means that the quality of data is relevant in the results. However, with more information it is possible classify 42% of fermentations (10/24 fermentations), 56% of normal fermentations and 33% of problematic fermentations. 4 Conclusions In the case studied here, three PCs were enough to preserve the relevant information contained in the raw data and achieve optimum classification using a dataset with reliable information. In addition, when unreliable measurements were usedmore PCs Study of Principal Components on Classification of Problematic Wine Fermentations 43 were needed to obtain better results.
115–123 (1995) 10. : Using Analytic QP and Sparseness to Speed Training of Support Vector Machines. In: NIPS conference, pp. 557–563 (1999) 11. 5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo (1993) Electronic Nose Ovarian Carcinoma Diagnosis 23 12. : Inductive functional programming using incremental program transformation. Artificial Intelligence 1, 55–83 (1995) 13. : Automatic Design of Pulse Coupled Neurons for Image Segmentation. Neurocomputing - Special Issue for Vision Research (2008) 14.