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Titlebook: Artificial Intelligence and Soft Computing; 15th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

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41#
發(fā)表于 2025-3-28 15:23:16 | 只看該作者
42#
發(fā)表于 2025-3-28 20:51:59 | 只看該作者
Fachbegriffe Finanz- und Rechnungswesen measures based on structural properties also involving psychological-cognitive aspects of similarity determination, and investigate admissible conversions. Finally, we discuss some consequences of the obtained taxonomy and their implications for machine learning algorithms.
43#
發(fā)表于 2025-3-28 23:49:27 | 只看該作者
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發(fā)表于 2025-3-29 06:37:57 | 只看該作者
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/162302.jpg
45#
發(fā)表于 2025-3-29 09:36:28 | 只看該作者
https://doi.org/10.1007/978-3-319-39384-1artificial neural networks; fuzzy logic; machine learning; particle swarm optimization; recommender syst
46#
發(fā)表于 2025-3-29 14:05:44 | 只看該作者
47#
發(fā)表于 2025-3-29 15:39:28 | 只看該作者
Improving Automatic Classifiers Through Interaction the number of queries to the oracle. We have tested our proposal by using twenty data sets and two adaptive classifiers from the Massive Online Analysis (MOA) open source framework for data stream mining.
48#
發(fā)表于 2025-3-29 23:30:16 | 只看該作者
Complexity of Rule Sets Induced from Data Sets with Many Lost and Attribute-Concept Valuese attribute-value. Our secondary objective is to test which of the three probabilistic approximations used for the experiments provide the simplest rule sets: singleton, subset or concept. The subset probabilistic approximation is the best, with 5?% significance level.
49#
發(fā)表于 2025-3-30 02:50:23 | 只看該作者
50#
發(fā)表于 2025-3-30 05:00:55 | 只看該作者
Text Mining with Hybrid Biclustering Algorithmse proposed method automatically reveals words appearing together in multiple texts. The proposed approach is compared to some of the most recognized clustering algorithms and shows the advantage of biclustering over clustering in text mining. Finally, the method is confronted with other biclustering methods in the task of classification.
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