Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

“…After the image has been pre-processed, it is segmented using the Thresholding Level set approach. Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”

Average number of selected features. by Guangwei Liu (181992)

“…Drawing inspiration from the Chinese idiom “Chai Lang Hu Bao,” hybrid algorithm mechanisms, and cooperative behaviors observed in natural animal populations, we amalgamate the GWO algorithm, the Lagrange interpolation method, and the GJO algorithm to propose the multi-strategy fusion GJO-GWO algorithm. …”

Average number of selected features. by Guangwei Liu (181992)

“…Drawing inspiration from the Chinese idiom “Chai Lang Hu Bao,” hybrid algorithm mechanisms, and cooperative behaviors observed in natural animal populations, we amalgamate the GWO algorithm, the Lagrange interpolation method, and the GJO algorithm to propose the multi-strategy fusion GJO-GWO algorithm. …”

The computational time of feature extraction for a single trial across different time segments. by Ebru Ergün (21395498)

Optimized model prediction performance. by Guang Tu (22054865)

Age feature importance. by Nicola Lazzarini (3528197)

Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

“…After the image has been pre-processed, it is segmented using the Thresholding Level set approach. Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. …”

Data_Sheet_1_How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework.ZIP by Hao Wu (65943)

Table_1_Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.XLSX by Qin-Yu Zhao (10014626)

Table_2_Development and Validation of a Machine-Learning Model for Prediction of Extubation Failure in Intensive Care Units.DOCX by Qin-Yu Zhao (10014626)

Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE by Subhashree Mohapatra (17387852)

“…The proposed framework leverages a strong categorical boosting (CatBoost) algorithm optimized using Grid Search Optimization (GSO). …”

Table_3_Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models.docx by Lei Chen (54296)

Table_2_Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models.docx by Lei Chen (54296)

Table_1_Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models.xlsx by Lei Chen (54296)

Table_4_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX by Josefa Díaz-Álvarez (5572427)

“…<p>Genetic algorithms have a proven capability to explore a large space of solutions, and deal with very large numbers of input features. …”

Table_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX by Josefa Díaz-Álvarez (5572427)

“…<p>Genetic algorithms have a proven capability to explore a large space of solutions, and deal with very large numbers of input features. …”

Table_2_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX by Josefa Díaz-Álvarez (5572427)

“…<p>Genetic algorithms have a proven capability to explore a large space of solutions, and deal with very large numbers of input features. …”

Table_5_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.docx by Josefa Díaz-Álvarez (5572427)

“…<p>Genetic algorithms have a proven capability to explore a large space of solutions, and deal with very large numbers of input features. …”

Table_3_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX by Josefa Díaz-Álvarez (5572427)

“…<p>Genetic algorithms have a proven capability to explore a large space of solutions, and deal with very large numbers of input features. …”

Table_1_Construction of a risk screening and visualization system for pulmonary nodule in physical examination population based on feature self-recognition machine learning model.X... by Fang Tian (360682)