Convergence graphs for ten CEC 2019 benchmark functions and direct comparison between COFFO and FFO. by Nebojsa Bacanin (13932723)

Subjects:

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

Parameter settings of the comparison algorithms. by Ying Li (38224)

“…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”

Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF by Maya Khatun (7437011)

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…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. …”

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

Image processing workflow. by Denis Tamiev (7404980)

“…<p>Raw fluorescent microscope images (a) were processed with a binary segmentation algorithm, and clusters of bacterial cells were manually annotated. …”

Confusion matrix for a binary outcome (adapted from Fawcett [30]). by João Albuquerque (12936572)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses by Meichen Liu (8168148)

Data_Sheet_1_Posiform planting: generating QUBO instances for benchmarking.pdf by Georg Hahn (12530469)

IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

“…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. …”

IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

“…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. …”

Convergence curve of feature selection algorithms across 11 datasets with KNN classifier. by Yi Wei Tye (22208735)

Top-performing model configuration and performance by algorithm type. by Uğur Ejder (22683228)

Subjects:

Proposed Algorithm. by Hend Bayoumi (22693738)

“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. EHRL integrates Reinforcement Learning (RL) with Deep Neural Networks (DNNs) to dynamically optimize binary offloading decisions, which in turn obviates the requirement for manually labeled training data and thus avoids the need for solving complex optimization problems repeatedly. …”

Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf by Sai Sakunthala Guddanti (17739363)

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data by Changhun Kim (682542)

“…However, ToxCast assays differ in the amount of data and degree of class imbalance (CI). Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …”

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

“…This result reflects the effectiveness of the algorithm, which provides a basis for the effective analysis and processing of image big data.…”

DataSheet1_Quantum-inspired optimization for wavelength assignment.PDF by Aleksey S. Boev (14441805)