Summary of the feature selection algorithms. by Martin Kostadinov (20410120)

Feature selection using Boruta algorithm. by Shayla Naznin (13014015)

“…</p><p>Methods</p><p>Multiple machine learning (ML) algorithms were applied to data from the 2022 Bangladesh Demographic Health Survey, including Random Forest, Decision Tree, K-Nearest Neighbors, Logistic Regression, Support Vector Machine, XGBoost, LightGBM and Neural Networks. …”

In Silico Sorghum GxExM Dataset For Prediction Algorithm Comparisons by Owen Powell (16328658)

“…<p><br></p><p dir="ltr"># In Silico Sorghum GxExM Dataset For Prediction Algorithm Comparisons</p><p><br></p><p dir="ltr">## Background</p><p dir="ltr">A simulated Multi-Environment Trial (MET) dataset to stimulate the development and comparisons of predictive algorithms to deconvolute genotype-by-environment-by-management interactions in plant breeding. …”

Data Sheet 1_Predictive model establishment for forward-head posture disorder in primary-school-aged children based on multiple machine learning algorithms.csv by Hongjun Tao (21448853)

“…Multiple machine learning algorithms are applied to construct distinct risk prediction models, with the most effective model selected through comparative analysis. …”

Details of multiple GWO algorithm variants. by Genliang Li (5816264)

Overall performance evaluation on the validation data. by Mohd Sakib (20565228)

Overall performance evaluation of the training data. by Mohd Sakib (20565228)

Performance comparison of ML algorithms across multiple evaluation metrics. by Muhammad Tausif (12385892)

Plot for whole validation data for weekend training. by Mohd Sakib (20565228)

Performance evaluation of four samples on the validation data. by Mohd Sakib (20565228)

Plot for whole validation data for weekdays training. by Mohd Sakib (20565228)

Pattern of the training and validating data for the last two months. by Mohd Sakib (20565228)

Fits of selected conformations to experimental SANS data. by Samuel Eriksson Lidbrink (21616146)

Using synthetic data to test group-searching algorithms in a context where the correct grouping of species is known and uniquely defined. by Yuanchen Zhao (12905580)

Subjects:

Comparison of prediction results from multiple models. by Wenguang Li (6528113)

Pairwise distance distribution of the selected conformations compared to the experimental data. by Samuel Eriksson Lidbrink (21616146)

Initial model prediction results. by Qun Zhao (603175)

“…Firstly, we utilize existing geographic and topographic indicators to identify and select watersheds that exhibit similarities. Subsequently, we establish an initial regression model using the TrAdaBoost algorithm based on the hydrologic data from the selected watershed stations. …”

Data Sheet 1_An individualized risk prediction tool for ectopic pregnancy within the first 10 weeks of gestation based on machine learning algorithms.docx by Xin Du (208780)

Weekdays and weekend patterns for net demand. by Mohd Sakib (20565228)

“…This study proposes an ensemble approach that integrates a genetic algorithm with multiple forecasting models to optimize feature selection. …”

Wilcoxon signed-rank test results. by Mohd Sakib (20565228)

“…This study proposes an ensemble approach that integrates a genetic algorithm with multiple forecasting models to optimize feature selection. …”