The effect of data resampling methods in radiomics
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-53491-5
Abstract: Radiomic datasets can be class-imbalanced, for instance, when the prevalence of diseases varies notably, meaning that the number of positive samples is much smaller than that of negative samples. In these cases, the majority class… read more here.
Keywords: selected features; data resampling; resampling methods; effect data ... See more keywords
Resampling methods with multiply imputed data.
Sign Up to like & getrecommendations! Published in 2025 at "Biometrika"
DOI: 10.1093/biomet/asaf059
Abstract: Resampling techniques have become increasingly popular for estimation of uncertainty. However, data are often fraught with missing values that are commonly imputed to facilitate analysis. This article addresses the issue of using resampling methods such… read more here.
Keywords: jackknife bootstrap; imputed data; resampling methods; multiply imputed ... See more keywords
Comparing Different Resampling Methods in Predicting Students’ Performance Using Machine Learning Techniques
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2986809
Abstract: In today’s world, due to the advancement of technology, predicting the students’ performance is among the most beneficial and essential research topics. Data Mining is extremely helpful in the field of education, especially for analyzing… read more here.
Keywords: different resampling; performance; machine; students performance ... See more keywords
Internet Financial Credit Scoring Models Based on Deep Forest and Resampling Methods
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3239889
Abstract: In recent years, deep learning credit scoring models have become a hot research topic in Internet finance. However, most of the existing studies are based on deep neural network models, whose structure is difficult to… read more here.
Keywords: credit; credit scoring; resampling methods; deep forest ... See more keywords
An Evaluation of Four Resampling Methods Used in Machine Learning Classification
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Intelligent Systems"
DOI: 10.1109/mis.2020.2978066
Abstract: This article investigates resampling methods used to evaluate the performance of machine learning classification algorithms. It compares four key resampling methods: 1) Monte Carlo resampling, 2) the Bootstrap Method, 3) k-fold Cross Validation, and 4)… read more here.
Keywords: classification; machine learning; resampling methods; four resampling ... See more keywords
Predicting defects in imbalanced data using resampling methods: an empirical investigation
Sign Up to like & getrecommendations! Published in 2022 at "PeerJ Computer Science"
DOI: 10.7717/peerj-cs.573
Abstract: The development of correct and effective software defect prediction (SDP) models is one of the utmost needs of the software industry. Statistics of many defect-related open-source data sets depict the class imbalance problem in object-oriented… read more here.
Keywords: software; defects imbalanced; resampling methods; predicting defects ... See more keywords