The data processing and analysis pipeline. by Xin Zhang (35492)

Data_Sheet_1_Crystal Structure Prediction of Binary Alloys via Deep Potential.PDF by Haidi Wang (9694004)

Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19. by Jiaqing Luo (10975030)

IRBMO vs. variant comparison adaptation data. 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. …”

MCLP_quantum_annealer_V0.5 by Anonymous Anonymous (4854526)

LITNET-2020 data splitting approach. by Asmaa Ahmed Awad (16726315)

The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... by Aninda Astuti (21736334)

Supplementary Material 8 by Nishitha R Kumar (19750617)

“…</li><li><b>XGboost: </b>An optimized gradient boosting algorithm that efficiently handles large genomic datasets, commonly used for high-accuracy predictions in <i>E. coli</i> classification.…”

Fig 1 - by Jakub Stoklosa (3315042)

Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. by Ramsés Noguez Imm (6658637)

Pseudo Code of RBMO. 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. …”

P-value on CEC-2017(Dim = 30). 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. …”

Memory storage behavior. 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. …”

Elite search behavior. 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. …”

Description of the datasets. 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. …”

S and V shaped transfer functions. 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. …”

S- and V-Type transfer function diagrams. 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. …”

Collaborative hunting behavior. 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. …”

Friedman average rank sum test results. 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. …”

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)