Search alternatives:
final classification » binary classification (Expand Search), image classification (Expand Search), risk classification (Expand Search)
based optimization » whale optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based final » based vaginal (Expand Search), based binary (Expand Search), based finite (Expand Search)
binary 2 » binary _ (Expand Search), binary b (Expand Search)
2 based » _ based (Expand Search), 1 based (Expand Search), ai based (Expand Search)
final classification » binary classification (Expand Search), image classification (Expand Search), risk classification (Expand Search)
based optimization » whale optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based final » based vaginal (Expand Search), based binary (Expand Search), based finite (Expand Search)
binary 2 » binary _ (Expand Search), binary b (Expand Search)
2 based » _ based (Expand Search), 1 based (Expand Search), ai based (Expand Search)
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IRBMO vs. meta-heuristic algorithms boxplot.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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IRBMO vs. feature selection algorithm boxplot.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
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Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF
Published 2019“…This method is implemented in PyAR (https://github.com/anooplab/pyar) program. The global optimization in PyAR involves two parts, generation of several trial geometries and gradient-based local optimization of the trial geometries. …”
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Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data
Published 2021“…In this article, we develop a novel angle-based approach to search the optimal DTR under a multicategory treatment framework for survival data. …”
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Data_Sheet_1_Calcium Spark Detection and Event-Based Classification of Single Cardiomyocyte Using Deep Learning.pdf
Published 2021“…Furthermore, we proposed an event-based logistic regression and binary classification model to classify single cardiomyocytes using Ca<sup>2+</sup> spark characteristics, which to date have generally been used only for simple statistical analyses and comparison between normal and diseased groups. …”
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Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
Published 2021“…<p>(A). The MCDM algorithm-Stage 1. Preprocessing, this stage is the process of refining the collected raw data to eliminate noise, including correlation analysis and feature selection based on P values. …”