a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset. حسب Nebojsa Bacanin (13932723)

الموضوعات:

Boxplots analysis of the tested algorithms using average error rate across 21 datasets. حسب Nebojsa Bacanin (13932723)

الموضوعات:

Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level حسب Giovanni Nattino (561797)

"…We implement the evidence factors method for binary outcomes, which includes a randomization-based testing strategy and a sensitivity analysis for hidden bias in three-group matched designs. …"

S1 Dataset - Novel chaotic oppositional fruit fly optimization algorithm for feature selection applied on COVID 19 patients’ health prediction حسب Nebojsa Bacanin (13932723)

الموضوعات:

The result of the best fitness value, mean fitness value, standard deviation of fitness value and feature selection ratio of algorithms on the COVID-19 dataset. حسب Nebojsa Bacanin (13932723)

الموضوعات:

CEC 2019 benchmark characteristics. حسب Nebojsa Bacanin (13932723)

الموضوعات:

Results of Holm’s step-down procedure. حسب Nebojsa Bacanin (13932723)

الموضوعات:

Friedman ranks of tested methods on CEC2019 benchmark functions. حسب Nebojsa Bacanin (13932723)

الموضوعات:

V-shaped transfer functions. حسب Nebojsa Bacanin (13932723)

الموضوعات:

Resilts of Friedman and Iman-Davenport tests (<i>α</i> = 0.05). حسب Nebojsa Bacanin (13932723)

الموضوعات:

Mean fitness and standard deviation results of compared approaches on CEC2019 benchmark functions. حسب Nebojsa Bacanin (13932723)

الموضوعات:

Error rate convergence graphs. حسب Nebojsa Bacanin (13932723)

الموضوعات:

COVID-19 dataset description. حسب Nebojsa Bacanin (13932723)

الموضوعات:

Control parameter settings for comparative feature selection methods. حسب Nebojsa Bacanin (13932723)

الموضوعات:

The result of the Wilcoxon test of presented COFFO against compared methods. حسب Nebojsa Bacanin (13932723)

الموضوعات:

COFFO control parameters. حسب Nebojsa Bacanin (13932723)

الموضوعات:

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

الموضوعات:

Algorithm for generating hyperparameter. حسب Balraj Preet Kaur (20370832)

"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Results of machine learning algorithm. حسب Balraj Preet Kaur (20370832)

"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"