Results 1 to 10 of about 38,704 (184)
Precise Undersampling Theorems [PDF]
Proceedings of the IEEE, 2010 Undersampling theorems state that we may gather far fewer samples than the usual sampling theorem while exactly reconstructing the object of interest-provided the object in question obeys a sparsity condition, the samples measure appropriate linear combinations of signal values, and we reconstruct with a particular nonlinear procedure.
David L Donoho, Jared Tanner
exaly +3 more sources
Phase-synchronous undersampling in nonlinear spectroscopy [PDF]
Optics Letters, 2018 We introduce the concept of phase-synchronous undersampling in nonlinear spectroscopy. The respective theory is presented and validated experimentally in a phase-modulated quantum beat experiment by sampling high phase modulation frequencies with low ...
Binz, Marcel +2 more
core +5 more sources
Undersampling and the inference of coevolution in proteins [PDF]
Cell Systems, 2021 Abstract Protein structure, function, and evolution depend on local and collective epistatic interactions between amino acids. A powerful approach to defining these interactions is to construct models of couplings between amino acids that reproduce the empirical statistics (frequencies and correlations) observed in sequences comprising ...
Kleeorin, Yaakov +3 more
openaire +3 more sources
Resampling Imbalanced Network Intrusion Datasets to Identify Rare Attacks
Future Internet, 2023 This study, focusing on identifying rare attacks in imbalanced network intrusion datasets, explored the effect of using different ratios of oversampled to undersampled data for binary classification. Two designs were compared: random undersampling before
Sikha Bagui +4 more
doaj +1 more source
The European Zoological Journal, 2023 The Bray–Curtis dissimilarity is widely used to calculate β diversity on abundance data. However, the effect of undersampling on this index has received limited attention and only few studies addressed this topic. The paper aimed to investigate the error
S. Hardersen, G. La Porta
doaj +1 more source
Improving Software Defect Prediction in Noisy Imbalanced Datasets
Applied Sciences, 2023 Software defect prediction is a popular method for optimizing software testing and improving software quality and reliability. However, software defect datasets usually have quality problems, such as class imbalance and data noise.
Haoxiang Shi +3 more
doaj +1 more source
Neural Network-Based Undersampling Techniques [PDF]
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022 8 pages in IEEE ...
Md. Adnan Arefeen +2 more
openaire +2 more sources
ComTech, 2020 The research conducted undersampling and gene selection as a starting point for cancer classification in gene expression datasets with a high-dimensional and imbalanced class.
Masithoh Yessi Rochayani +2 more
doaj +1 more source
Universal Undersampled MRI Reconstruction [PDF]
, 2021 Deep neural networks have been extensively studied for undersampled MRI reconstruction. While achieving state-of-the-art performance, they are trained and deployed specifically for one anatomy with limited generalization ability to another anatomy.
Xinwen Liu 0003 +3 more
openaire +3 more sources
Presumably Correct Undersampling
, 2023 This paper presents a data pre-processing algorithm to tackle class imbalance in classification problems by undersampling the majority class. It relies on a formalism termed Presumably Correct Decision Sets aimed at isolating easy (presumably correct) and difficult (presumably incorrect) instances in a classification problem.
Gonzalo Nápoles, Isel Grau
openaire +1 more source