Download Artificial Intelligence and Soft Computing: 13th by Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard PDF

By Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada

The two-volume set LNAI 8467 and LNAI 8468 constitutes the refereed court cases of the thirteenth overseas convention on synthetic Intelligence and delicate Computing, ICAISC 2014, held in Zakopane, Poland in June 2014. The 139 revised complete papers provided within the volumes, have been rigorously reviewed and chosen from 331 submissions. The sixty nine papers incorporated within the first quantity are inquisitive about the next topical sections: Neural Networks and Their purposes, Fuzzy structures and Their functions, Evolutionary Algorithms and Their functions, category and Estimation, laptop imaginative and prescient, photo and Speech research and particular consultation three: clever tools in Databases. The seventy one papers within the moment quantity are equipped within the following topics: info Mining, Bioinformatics, Biometrics and clinical purposes, Agent platforms, Robotics and keep an eye on, man made Intelligence in Modeling and Simulation, numerous difficulties of man-made Intelligence, specific consultation 2: computer studying for visible details research and defense, distinct consultation 1: purposes and homes of Fuzzy Reasoning and Calculus and Clustering.

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Extra info for Artificial Intelligence and Soft Computing: 13th International Conference, ICAISC 2014, Zakopane, Poland, June 1-5, 2014, Proceedings, Part II

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Let D denote a database with customers d1 -dn and a non-customer d0 . Each customer di has variables first call f irsti and last call lasti . for each line l ∈ CDR1 do if caller di ∈ D then lasti = date1 D = D ∪ {di } Algorithm 2. Determine the Churn Class for a set of Customers Input: Call Detail Records and Customer Database Output: Customer Database Subsets Assume CDRm and D from Algorithm 1 exist. Now let D = C ∪ N , such that C contains first month churners. The binary variable churni indicates churn or non-churn during the entire study.

The conjecture is that a well-behaving categorization procedure should be well-reproducible using typical classifier construction algorithms. The ordered nature of classes is discarded by all common classification algorithms. As a result all misclassifications are treated as equally undesirable which is not true. More appropriate algorithms would take the ordering into account. We have selected GWO SI1EA as input data (ID and four basic criteria). During learning we use 4-fold cross-validation due to small size of the sample.

Of the Indian Conference on Computer Vision, Graphics and Image Processing (December 2008) 26. : Programs for machine learning. Morgan Kaufmann Publishers (1993) 27. VOC. zip 28. : Local features and kernels for classification of texture and object categories: a comprehensive study. be 2 School of Management, University of Southampton, UK Abstract. Customer retention has become a necessity in many markets, including mobile telecommunications. As it becomes easier for customers to switch providers, the providers seek to improve prediction models in an effort to intervene with potential churners.

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