By Janusz Sobecki, Veera Boonjing, Suphamit Chittayasothorn
This publication comprises 35 chapters providing assorted theoretical and sensible elements of clever info and Database structures. these days either clever and Database platforms are utilized in lots of the parts of human actions which necessitates additional study in those parts. during this publication quite a few fascinating matters with regards to the clever details types and techniques in addition to their complicated purposes, database structures purposes, facts versions and their research and electronic multimedia equipment and purposes are awarded and mentioned either from the sensible and theoretical issues of view. The e-book is equipped in 4 elements dedicated to clever platforms versions and techniques, clever platforms complex purposes, database structures equipment and purposes and multimedia structures tools and functions. The publication may be attention-grabbing for practitioners and researchers, in particular graduate and PhD scholars of data know-how and computing device technology, to boot more matured lecturers and experts attracted to constructing and verification of clever info, database and multimedia platforms versions, equipment and functions. The readers of this quantity are enabled to discover many inspiring rules and motivating functional examples that might aid them within the present and destiny work.
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Additional resources for Advanced Approaches to Intelligent Information and Database Systems
But at this stage we can recommend to use the RF-ODT algorithm. RF-ODT does no dominates SVM on all measures but it is slightly better for F1 and GMean and better for Accuracy correct. RF-ODT outperforms SVM in predicting correct answers and thus ask less the ERP consultant to check the corresponding questions, saving more consultant’s time. Taking into account these performances and after a discussion with ERP consultants it has been decided to select the RF-ODT algorithm. Table 2. Performance measure (in %) Algorithm Acc.
We seek an optimal algorithm to classify the conflict states by considering our model that resolves conflicts between two agents discussed in . In this paper, we extend the model to include conflicts between three or more agents. While we assume that the confidence value for each agent in the domain is known, the confidence value is different from other agents. The objective is to develop an optimal solution to the conflict classification problem, which provides a procedural approach to the classification and resolution of conflicts leading to a final decision.
96–103. ACM, New York (2008) 32. , De Vleeschouwer: Embedding proximal support vectors into randomized trees. In: European Symposium on Artiﬁcial Neural Networks, Advances in Computational Intelligence and Learning, Bruges, Belgium, pp. 373– 378 (2009) 33. : Classifying very-high-dimensional data with random forests of oblique decision trees. , Briand, H. ) Advances in Knowledge Discovery and Management. SCI, vol. 292, pp. 39–55. Springer, Heidelberg (2010) 34. : Bagging predictors. Technical Report 421, Department of Statistics University of California, Berkeley, California 94720 USA (1994) 35.
Advanced Approaches to Intelligent Information and Database Systems by Janusz Sobecki, Veera Boonjing, Suphamit Chittayasothorn