Data generation algorithm. حسب Aluwani Ramalata (21262977)

Pseudocode for the missForestPredict algorithm. حسب Elena Albu (15181070)

"…The algorithm iteratively imputes variables using random forests until a convergence criterion, unified for continuous and categorical variables, is met. …"

The relevant data file for this article. حسب Linsha Liu (20378293)

Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms حسب Zahra Bastami (21474755)

Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms حسب Zahra Bastami (21474755)

Feature selection using Boruta algorithm. حسب 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. …"

Schematic diagram of random forest algorithm. حسب Imee V. Necesito (12749885)

Ranking of ML algorithms. حسب 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. …"

Relevant computed image data. حسب Zhaoyu Ku (20660546)

Definitions of relevant SSA parameters. حسب Yeping Shi (14279118)

الموضوعات:

The overview of the ML algorithms’ flowchart. حسب 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. …"

The relevant code in the manuscript can be found in the supporting information data file. حسب Xini Fang (20861990)

الموضوعات:

The AUC of each model was calculated using 113 ML algorithm. حسب Xuefen Lin (17785367)

الموضوعات:

Feature selection using the Boruta algorithm. حسب Guang Tu (22054865)

"…We extracted baseline characteristics, laboratory parameters, and clinical outcomes. The Boruta algorithm was employed for feature selection to identify variables significantly associated with in-hospital mortality, and 16 machine learning models, including logistic regression, random forest, gradient boosting, and neural networks, were developed and compared using receiver operating characteristic (ROC) curves and area under the curve (AUC) analysis. …"

Explained variance ration of the PCA algorithm. حسب Abeer Aljohani (18497914)

"…The spectral coefficients are based on an orthogonal system of Legendre type smooth polynomials. We developed the mathematical theory to calculate spectral moment in Legendre polynomails space and use these moments to train traditional classifier like SVM and random forest for a classification task. …"

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

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

"…<div><p>Background and objectives</p><p>Child undernutrition is a leading global health concern, especially in low and middle-income developing countries, including Bangladesh. 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.…"

Comparison of information on predicting survival outcomes or metastasis of cancer patients using machine learning algorithms in the past. حسب Jingru Dong (14076094)

الموضوعات:

Data Sheet 1_Algorithmic esthetics meets human intuition: the synergy of innovation and relevance shapes sustained attention.pdf حسب Wen Guan (5612195)

Genome-wide identification of candidate regions associated with birth weight in Lori-Bakhtiari sheep using Random Forest algorithm حسب Mohammad Hossein Moradi (11400671)

"…This study was conducted to identify genetic loci associated with birth weight in a meat-type sheep using a Random Forest (RF) algorithm applied to genomic data. …"