Search alternatives:
guided optimization » model optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary care » primary care (Expand Search), binary image (Expand Search), binary pairs (Expand Search)
care based » case based (Expand Search), score based (Expand Search), scale based (Expand Search)
guided optimization » model optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary care » primary care (Expand Search), binary image (Expand Search), binary pairs (Expand Search)
care based » case based (Expand Search), score based (Expand Search), scale based (Expand Search)
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1
The Pseudo-Code of the IRBMO Algorithm.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. meta-heuristic algorithms boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. feature selection algorithm boxplot.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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IRBMO vs. variant comparison adaptation data.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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Pseudo Code of RBMO.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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P-value on CEC-2017(Dim = 30).
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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10
Memory storage behavior.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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11
Elite search behavior.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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12
Description of the datasets.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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13
S and V shaped transfer functions.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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14
S- and V-Type transfer function diagrams.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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15
Collaborative hunting behavior.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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16
Friedman average rank sum test results.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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17
Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level
Published 2021“…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”
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