Comparison of methods on the Banana dataset. حسب Mohammed Shalaby (18297650)

Comparison of methods on the Adult9a dataset. حسب Mohammed Shalaby (18297650)

Description of the real-world dataset. حسب Fadi K. Dib (5204807)

"…Unlike most population-based methods, Jaya algorithm is a parameter-less algorithm in that it requires no algorithm-specific control parameters and only population size and number of iterations need to be specified, which makes it easy for researchers to apply in the field. …"

Screenshot of our visualization tool MGDrawVis. حسب Fadi K. Dib (5204807)

"…Unlike most population-based methods, Jaya algorithm is a parameter-less algorithm in that it requires no algorithm-specific control parameters and only population size and number of iterations need to be specified, which makes it easy for researchers to apply in the field. …"

DataSheet1_An optimized three-dimensional time-space domain staggered-grid finite-difference method.docx حسب Wei Liu (20030)

"…Examining the numerical dispersion, algorithm stability and computational cost, we compare our optimized time-space domain LS-based 3D SFD method with three conventional TE-based and LS-based 3D SFD methods to illustrate and demonstrate its effectiveness and feasibility. …"

Simultaneous Estimation of Connectivity and Dimensionality in Samples of Networks حسب Wenlong Jiang (5797223)

"…The method is formulated as a convex optimization problem and solved using an alternating direction method of multipliers algorithm. …"

DataSheet_1_Stronger wind, smaller tree: Testing tree growth plasticity through a modeling approach.docx حسب Haoyu Wang (429641)

"…The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is adopted to maximize the multi-objective function (stem biomass and tree height) by determining the key parameter value controlling the biomass allocation to the secondary growth. …"

A new GEE-based App called “Crop Mapper” for crop mapping حسب Anonymous During Peer Review (16029755)

"…</p> <p>The crop maps will be derived using the Random Forest machine learning algorithm and monthly gap-free Landsat Sentinel-2 time series data that was evaluated to be optimal and well documented in this paper. …"

Supporting data for "clinical-oriented surgical planning based on finite element method and automate-generated surgical templates assisting the spinal surgery" حسب Tianchi Wu (11062323)

"…Geodesic curvature was imported as optimization objective, while smooth coefficient and deviation allowance were defined to control the iteration loop. …"

DataSheet_1_CT-Based Radiomics Analysis for Preoperative Diagnosis of Pancreatic Mucinous Cystic Neoplasm and Atypical Serous Cystadenomas.pdf حسب Tiansong Xie (10959561)

"…Objectives<p>To investigate the value of CT-based radiomics analysis in preoperatively discriminating pancreatic mucinous cystic neoplasms (MCN) and atypical serous cystadenomas (ASCN).…"

Table_1_Viability Study of Machine Learning-Based Prediction of COVID-19 Pandemic Impact in Obsessive-Compulsive Disorder Patients.DOCX حسب María Tubío-Fungueiriño (12069125)

"…Machine learning may be valuable tool for helping clinicians to rapidly identify patients at higher risk and therefore provide optimized care, especially in future pandemics. However, further validation of these models is required to ensure greater reliability of the algorithms for clinical implementation to specific objectives of interest.…"

Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx حسب Changjiang Liang (21099887)

"…In addition, YOLOv8-FPDW was more competitive than mainstream object detection algorithms. The study predicted the optimal harvest period for litchis, providing scientific support for orchard batch harvesting and fine management.…"

Data_Sheet_1_Development and validation of prediction models for hypertension risks: A cross-sectional study based on 4,287,407 participants.docx حسب Weidong Ji (129916)

"…Objective<p>To develop an optimal screening model to identify the individuals with a high risk of hypertension in China by comparing tree-based machine learning models, such as classification and regression tree, random forest, adaboost with a decision tree, extreme gradient boosting decision tree, and other machine learning models like an artificial neural network, naive Bayes, and traditional logistic regression models.…"

Data Sheet 1_Machine learning-based ultrasomics for predicting response to tyrosine kinase inhibitor in combination with anti-PD-1 antibody immunotherapy in hepatocellular carcinom... حسب Yiwen Hu (615619)

"…Objective<p>The objective of this study is to build and verify the performance of machine learning-based ultrasomics in predicting the objective response to combination therapy involving a tyrosine kinase inhibitor (TKI) and anti-PD-1 antibody for individuals with unresectable hepatocellular carcinoma (HCC). …"

Table_1_Reorganization of the Brain Structural Covariance Network in Ischemic Moyamoya Disease Revealed by Graph Theoretical Analysis.docx حسب Peijing Wang (12716633)

"…Structural images were pre-processed using the Computational Anatomy Toolbox 12 (CAT 12) based on the diffeomorphic anatomical registration through exponentiated lie (DARTEL) algorithm and both the global and regional SCN parameters were calculated and compared using the Graph Analysis Toolbox (GAT).…"

GA-XGBoost confusion matrix. حسب Ke Peng (2220973)

"…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …"

Details of feature variables of the data set. حسب Ke Peng (2220973)

"…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …"

Comparison results of each classification model. حسب Ke Peng (2220973)

"…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …"

ROC curve of models. حسب Ke Peng (2220973)

"…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …"

Comparison results of different model. حسب Ke Peng (2220973)

"…The results show that: (1) The applied SMOTEENN is more effective than SMOTE and ADASYN in dealing with the imbalance of banking data. (2) The F1 and AUC values of the model improved and optimized by XGBoost using genetic algorithm can reach 90% and 99%, respectively, which are optimal compared to other six machine learning models. …"