Table_4_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”

Table_2_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”

Table_6_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”

Table_10_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”

Table_3_Preliminary prediction of semen quality based on modifiable lifestyle factors by using the XGBoost algorithm.docx by Mingjuan Zhou (12880019)

“…Then, machine learning with the XGBoost algorithm was applied to establish a primary prediction model by using the collected data. …”

Data_Sheet_1_Prediction of Mental Health in Medical Workers During COVID-19 Based on Machine Learning.ZIP by Xiaofeng Wang (119575)

“…In this study, we propose a novel prediction model based on optimization algorithm and neural network, which can select and rank the most important factors that affect mental health of medical workers. …”

Models’ performance without optimization. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

Raw results. by Mahmood A. Jumaah (22272371)

RNN performance comparison with/out optimization. by Muhammad Usman Tariq (11022141)

“…These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. …”

Image_1_The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.TIF by Xiaoying Lou (9700261)

Image_2_The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.TIF by Xiaoying Lou (9700261)

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)

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

“…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …”

Table_1_Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.docx by Liyin Zhang (6371999)

Load data or power demand. by M. Nasrallah (19066121)

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

A portfolio selection model based on the knapsack problem under uncertainty by Fereshteh Vaezi (6655028)

“…The resulted model is converted into a parametric linear programming model in which the decision maker is able to determine the optimism threshold. Finally, a discrete firefly algorithm is designed to find the near optional solutions in large dimensions. …”

Weights of sample data. by Yixuan Lu (9987980)

Summary of existing CNN models. by Nicodemus Songose Awarayi (18414494)

“…The model further showed superior results on binary classification compared with existing methods. …”

Data_Sheet_1_Prediction-Driven Decision Support for Patients With Mild Stroke: A Model Based on Machine Learning Algorithms.docx by Xinping Lin (1591438)