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This imbalanced performance is really not that surprising.
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Nevertheless, the existing traditional SPC schemes for bivariate quality control (BQC) were mainly designed for rapid detection of unnatural variation with limited capability in avoiding false alarm, that is, imbalanced monitoring performance.
This optimal control strategy is important for decreasing the annual ground thermal imbalance performance of ground boreholes.
When there is an imbalance, performance asymptotes at a level reflecting the degree of imbalance (as well as the strength of the stimulus information), in accordance with the pattern seen in behavioral experiments [1].
The increase in cross-validation value aids to improve classification performance of imbalanced data sets by decreasing bias.
BC techniques have been shown to efficiently integrate the responses of multiple diversified classifiers in the ROC space, yet the impact on performance of imbalanced data distributions is difficult to observe from ROC curves.
A kappa statistic quantifies the improvement of the classifier compared with a random classifier, which can be a robust measure to evaluate overall classifier performance for imbalanced datasets [ 34].
As accuracy alone is not a good indicator of performance within imbalanced data sets (the classifier could achieve high accuracy by always classifying scenes as Potentials) we also assessed sensitivity.
Thus, they generally perform poor performance on the imbalanced datasets.
The six individual methods used in the ensemble methods may not be the best choice, since their performances were imbalanced, i.e. a large discrepancy in accuracy between PFP/ESG and the rest of the methods.
Balanced Accuracy (BAC) avoids magnifying performance estimates of imbalanced datasets.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com