Algorithm of model development and validation. by Bethan Cracknell Daniels (20469396)

Random Forest and Gradient Boosting algorithms. by Yvan J. Garcia-Lopez (20783591)

CatBoost algorithm structure to predict clinical outcome. by Andrew McDonald (2307400)

Subjects:

The pseudocode of the RFE algorithm. by Zuzhen Ji (17593348)

Data on the prediction performances of ML algorithms. by Yasemin Ayaz Atalan (21989402)

The steps of applying RF algorithm. by Zuzhen Ji (17593348)

Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

Subjects:

Ranking of ML algorithms. by Yasemin Ayaz Atalan (21989402)

“…For this purpose, well-known Machine Learning (ML) algorithms such as Random Forest (RF), Adaptive Boosting (AB), and Gradient Boosting (GB) were utilized. …”

Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.…”

The overview of the ML algorithms’ flowchart. by Yasemin Ayaz Atalan (21989402)

“…For this purpose, well-known Machine Learning (ML) algorithms such as Random Forest (RF), Adaptive Boosting (AB), and Gradient Boosting (GB) were utilized. …”

Statistics of the predictive performance indicators of four different competitor algorithms. by Jin Wang (29560)

Subjects:

General model performance for different algorithms. by Binghan Xue (21253235)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Data Sheet 1_Interpretable machine learning algorithms reveal gut microbiome features associated with atopic dermatitis.docx by Jingtai Ma (21225476)

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”

DataSheet1_Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm.docx by Qiyuan Cui (19729288)

“…Objective<p>The aim of this study was to develop and validate a machine learning-based model to predict the development of impaired fasting glucose (IFG) in middle-aged and older elderly people over a 5-year period using data from a cohort study.…”

Decision tree algorithms. by Mahbub E. Sobhani (22278967)

“…We have used Random Forest, Bagging, and Boosting (AdaBoost) algorithms and have compared their performances. …”

Comparison of the performance of ML algorithms in predicting maize yield using 5-fold CV. by Oumnia Ennaji (20442244)

Data Sheet 1_Enhancing fever of unknown origin diagnosis: machine learning approaches to predict metagenomic next-generation sequencing positivity.docx by Zhi Gao (257044)