Titlebook: Computational Science – ICCS 2020; 20th International C Valeria V. Krzhizhanovskaya,Gábor Závodszky,João T Conference proceedings 2020 Spri

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书目名称Computational Science – ICCS 2020影响因子(影响力)




书目名称Computational Science – ICCS 2020影响因子(影响力)学科排名




书目名称Computational Science – ICCS 2020网络公开度




书目名称Computational Science – ICCS 2020网络公开度学科排名




书目名称Computational Science – ICCS 2020被引频次




书目名称Computational Science – ICCS 2020被引频次学科排名




书目名称Computational Science – ICCS 2020年度引用




书目名称Computational Science – ICCS 2020年度引用学科排名




书目名称Computational Science – ICCS 2020读者反馈




书目名称Computational Science – ICCS 2020读者反馈学科排名

贪心

Branch-and-Bound Search for Training Cascades of Classifiersuce the . used by an operating cascade—a key quantity we focus on in the paper. While searching, we observe suitable lower bounds on partial expectations and prune tree branches that cannot improve the best-so-far result. Both exact and approximate variants of the approach are formulated. Experiment

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CARK

Grammatical Inference by Answer Set Programming proposed in the literature is reformulated in two different ways: in terms of general constrains and as an answer set program. In a series of experiments, we showed that our answer set programming approach is much faster than our alternative method and the original SAT encoding method. Similarly to

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A Correction Method of a Base Classifier Applied to Imbalanced Data Classificationinition of the soft neighbourhood of the classified object. The first approach is to change the neighbourhood to be more local by changing the Gaussian potential function approach to the nearest neighbour rule. The second one is to weight the instances that are included in the neighbourhood. The ins

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in a Support-Domain of Fuzzy Classifier Prediction for the Task of Imbalanced Data Classificationads to favoring majority classes. The action most often used to deal with this problem is oversampling of the minority class by the . algorithm. Following work proposes to employ a modification of an individual binary classifier support-domain decision boundary, similar to the fusion of classifier e

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Employing One-Class SVM Classifier Ensemble for Imbalanced Data Stream Classificationresented, there are problems typical for data stream classification, such as limited resources, lack of access to the true labels and the possibility of occurrence of the .. Possibility of . appearing enforces design in the method adaptation mechanism. In this article, we propose the OCEIS classifie

prodrome

Clustering and Weighted Scoring in Geometric Space Support Vector Machine Ensemble for Highly Imbala problem of imbalanced data: algorithm-level and data-level solutions. This paper deals with the second approach. In particular, this paper shows a new proposition for calculating the weighted score function to use in the integration phase of the multiple classification system. The presented researc