Results 91 to 100 of about 4,590,312 (339)
Mitigating Class Imbalance in Time Series Classification via Generative Modeling
Most classification techniques assume a uniform distribution of training data classes. However, well-balanced data is rare, with infrequent events often being the most valuable.
Chen, Yang
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Molecular Oncology, EarlyView.Dormant cancer cells can hide in distant organs for years, evading treatment and the immune system. This review highlights how signals from the surrounding tissue and immune environment keep these cells inactive or trigger their reawakening. Understanding these mechanisms may help develop therapies to eliminate or control dormant cells and prevent ...
Kanishka Tiwary +1 more
wiley +1 more source
Symmetry, 2020 Software defect prediction (SDP) is the technique used to predict the occurrences of defects in the early stages of software development process. Early prediction of defects will reduce the overall cost of software and also increase its reliability. Most of the defect prediction methods proposed in the literature suffer from the class imbalance problem.
Kiran Kumar Bejjanki +2 more
openaire +1 more source
Molecular Oncology, EarlyView.A urine‐based digital PCR assay targeting two hotspot TERT promoter variants detected bladder cancer with high sensitivity and no false positives in this case–control cohort. The streamlined AbsoluteQ workflow outperformed Sanger sequencing and supports non‐invasive molecular testing for bladder cancer detection.
Anna Nykel +12 more
wiley +1 more source
Journal of ICTIn IoT environment applications generate continuous non-stationary data streams with in-built problems of concept drift and class imbalance which cause classifier performance degradation.
Abdul Sattar Palli +6 more
doaj +1 more source
Molecular Oncology, EarlyView.The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka +9 more
wiley +1 more source
Dealing with Class Imbalance using Thresholding
CoRR, 2016 We propose thresholding as an approach to deal with class imbalance. We define the concept of thresholding as a process of determining a decision boundary in the presence of a tunable parameter. The threshold is the maximum value of this tunable parameter where the conditions of a certain decision are satisfied.
Charmgil Hong +2 more
openaire +2 more sources
An Experimental Investigation of Calibration Techniques for Imbalanced Data
IEEE Access, 2020 Calibration is a technique used to obtain accurate probability estimation for classification problems in real applications. Class imbalance can create considerable challenges in obtaining accurate probabilities for calibration methods.
Lanlan Huang +4 more
doaj +1 more source
On the Performance of Oversampling Techniques for Class Imbalance Problems [PDF]
, 2020 Although over 90 oversampling approaches have been developed in the imbalance learning domain, most of the empirical study and application work are still based on the “classical” resampling techniques. In this paper, several experiments on 19 benchmark datasets are set up to study the efficiency of six powerful oversampling approaches, including both ...
Kong, J. +4 more
openaire +2 more sources
CARBO: Clustering and rotation based oversampling for class imbalance learning
Class imbalance of a data set is a crucial problem in machine learning where one class significantly outnumbers others. In such a data set, classification is a troublesome task for the standard classification algorithms, leading to bias towards the ...
Siddique, ASMMR +4 more
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