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Titlebook: Artificial Intelligence and Soft Computing; 19th International C Leszek Rutkowski,Rafa? Scherer,Jacek M. Zurada Conference proceedings 2020

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41#
發(fā)表于 2025-3-28 16:56:56 | 只看該作者
https://doi.org/10.1057/978-1-137-56554-9ormances of 8 prototype selection algorithms in terms of accuracy and reduction rate. The experimental results show that, in general, the proposed algorithm provides a good trade-off between reduction rate and the accuracy with reasonable time complexity.
42#
發(fā)表于 2025-3-28 21:45:19 | 只看該作者
https://doi.org/10.1057/978-1-137-56554-9the mentioned deficiencies via (1) restricting the number of links that can impact the pagerank (2) allowing for multistep linkage to be taken into account. The preliminary experiments on a large scale search engine data confirm the value of this new approach.
43#
發(fā)表于 2025-3-29 01:28:06 | 只看該作者
44#
發(fā)表于 2025-3-29 05:55:12 | 只看該作者
45#
發(fā)表于 2025-3-29 10:21:48 | 只看該作者
Classifying Image Series with a Reoccurring Concept Drift Using a Markov Chain Predictor as a Feedbaed not only to images but also to vectors of features arising in other applications. Additionally, this idea can be combined with any classifier that is able to take into account a priori probabilities. We provide an analysis when this approach leads to the reduction of the classification errors in
46#
發(fā)表于 2025-3-29 15:16:05 | 只看該作者
A Density-Based Prototype Selection Approachormances of 8 prototype selection algorithms in terms of accuracy and reduction rate. The experimental results show that, in general, the proposed algorithm provides a good trade-off between reduction rate and the accuracy with reasonable time complexity.
47#
發(fā)表于 2025-3-29 18:09:34 | 只看該作者
FlexTrustRank: A New Approach to Link Spam Combatingthe mentioned deficiencies via (1) restricting the number of links that can impact the pagerank (2) allowing for multistep linkage to be taken into account. The preliminary experiments on a large scale search engine data confirm the value of this new approach.
48#
發(fā)表于 2025-3-29 20:28:43 | 只看該作者
The Influence of Feature Selection on Job Clustering for an E-recruitment Recommender Systemre of the jobs; and the dataset resulting from the union of the two previous ones. The features’ subsets selected in each of the above scenarios had their performance evaluated in a clustering task. The results obtained in each scenario show a performance gain of the clustering process when feature
49#
發(fā)表于 2025-3-30 00:44:22 | 只看該作者
50#
發(fā)表于 2025-3-30 07:18:13 | 只看該作者
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