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A set of synthetic sample mixtures were used to validate the propose method.
The levels of impurity elements, primarily present as second-phase oxides and sulfides, were significantly higher in the natural FeS2 than in the synthetic sample.
Citric and malic acids in synthetic sample mixtures and in orange juices were analyzed and the performance of ANN was compared with that of partial least squares (PLS) regression.
A synthetic sample experiment is used to show that inclusion of nutrient availability is critical to reproduce carbonate lithofacies heterogeneity in a more accurate temporal and spatial disposition as a function of trophic resources.
The synthetic sample with the smallest particle size (30 nm in average — 39 m2/g) showed its entire surface area available for adsorption, despite its highly aggregated state observed, suggesting an open and highly dynamic aggregate framework.
The goal of this work is to propose REMEDIAL-HwR (REMEDIAL Hybridization with Resampling), a procedure to hybridize this method with some of the best resampling algorithms available in the literature, including random oversampling, heuristic undersampling and synthetic sample generation techniques.
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To tackle this problem, our over-sampling method generates synthetic samples which occupy more feature space than the other SMOTE algorithms.
The proposed over-sampling method generates useful synthetic samples for the classification of imbalanced biomedical data.
The experimental results on eight real-world benchmark datasets have shown that the proposed over-sampling method generates useful synthetic samples for the classification of imbalanced biomedical data.
Briefly saying, our over-sampling method enables to generate useful synthetic samples by referring to actual samples taken from real-world datasets.
Barua et al. developed a novel over-sampling method called MWMOTE [ 10], which generates synthetic samples in clusters of informative minority class samples.
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