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

CHIDE

K. G. Burra,P. Chandna,Ashwani K. Guptain relation to the evaluation metric used is affected by the change of the imbalance rate. Finally, we demonstrate that using subsampling in order to get a test dataset with class imbalance equal to the one observed in the wild is not necessary, and eventually can lead to significant errors in classifier’s performance estimate.

妨碍

alcohol-abuse

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Dynamic Classifier Selection for Data with Skewed Class Distribution Using Imbalance Ratio and Eucliles (.) and the other also considering those cases where the classifier makes a mistake. The proposed methods were evaluated based on computer experiments carried out on . datasets with a high imbalance ratio. The obtained results and statistical analysis confirm the usefulness of the proposed solutions.

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A Correction Method of a Base Classifier Applied to Imbalanced Data Classificationtances are weighted inversely proportional to the a priori class probability. The experimental results show that for one of the investigated base classifiers, the usage of the KNN neighbourhood significantly improves the classification results. What is more, the application of the weighting schema also offers a significant improvement.

Induction

in a Support-Domain of Fuzzy Classifier Prediction for the Task of Imbalanced Data Classificationnsembles done by the . method to deal with imbalanced data classification without introducing any repeated or artificial patterns into the training set. The proposed solution has been tested in computer experiments, which results shows its potential in the ..

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