Results 251 to 260 of about 106,507 (280)

To improve classification of imbalanced datasets

2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), 2017
The task of accurately predicting the target class for each case in the data is called classification of data in data mining. Classification of balanced data set is fairly simple and easy to perform but it becomes difficult when the data is not balanced.
Pratyusha Shukla, Kiran Bhowmick
openaire   +1 more source

Learning Curve Estimation with Large Imbalanced Datasets

2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA), 2019
Datasets for machine learning are constantly increasing in size, along with computational requirements for processing the data. A useful exercise for machine learning experiments is to approximate model performance as dataset size increases. This can inform application building and data collection efforts as well as improve computational efficiency by ...
Aaron N. Richter, Taghi M. Khoshgoftaar
openaire   +1 more source

Passive OS Identification in Imbalanced Dataset

2023 International Conference on Electrical, Computer and Energy Technologies (ICECET), 2023
Jingzhi Li, Ziling Wei, Shuhui Chen
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Optimisation and Evaluation of Random Forests for Imbalanced Datasets

2006
This paper deals with an optimization of Random Forests which aims at: adapting the concept of forest for learning imbalanced data as well as taking into account user's wishes as far as recall and precision rates are concerned. We propose to adapt Random Forest on two levels.
Julien Thomas, Pierre-Emmanuel Jouve, Nicolas Nicoloyannis   +2 more
openaire   +1 more source

A review of methods for imbalanced multi-label classification

Pattern Recognition, 2021
Adane Nega Tarekegn, Mario Giacobini, Krzysztof Michalak   +2 more
exaly  

Balancing techniques for imbalanced datasets

Proceedings of the 8th International Research Congress REDU, 2022
Luis Cedeño-Valarezo, Jessica Morales-Carrillo, César Andrade-Sánchez, Javier López-Zambrano   +3 more
openaire   +1 more source

TFSFB: Two-stage feature selection via fusing fuzzy multi-neighborhood rough set with binary whale optimization for imbalanced data

Information Fusion, 2023
Lin Sun, Weiping Ding
exaly  

A Survey of Predictive Modeling on Imbalanced Domains

ACM Computing Surveys, 2017
Paula Branco, Luis Torgo, Rita P Ribeiro   +2 more
exaly  

Learning from Imbalanced Data

IEEE Transactions on Knowledge and Data Engineering, 2009
Haibo He
exaly  

Machine Learning Model for the Imbalanced Dataset

2025 14th Mediterranean Conference on Embedded Computing (MECO)
Stanislav A. Krivenko, Liudmyla S. Kryvenko, Sergii S. Kryvenko   +2 more
openaire   +1 more source