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

Research on Differential Genes in Rheumatoid Arthritis Synovium Based on Multiple Machine Learning Algorithms by Fangzheng He (20736611)

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. …”

Run times of two algorithms. by Gourab Saha (8987405)

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A new approach in soil organic carbon estimation using machine learning algorithms: a study in a tropical forest in Vietnam by Thuy Phuong Nguyen (11769999)

“…This study aimed to evaluate the ability of SOC estimation using a multiple linear regression model (MLR) and four machine learning algorithms: artificial neural networks (ANN), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) with satellite data sources and soil nutrient indicator data to find the optimal method. …”

Sensor value scenario for fuzzy logic algorithm. by Gourab Saha (8987405)

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Sensor value scenario for average value algorithm. by Gourab Saha (8987405)

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Confusion matrix of random forest model. by Gourab Saha (8987405)

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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)

“…</p>Objective<p>This study aims to identify highly sensitive predictive indicators for forward head posture in primary school children using the Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithm. Multiple machine learning algorithms are applied to construct distinct risk prediction models, with the most effective model selected through comparative analysis. …”

Water consumption due to average value and fuzzy logic algorithm. by Gourab Saha (8987405)

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Crop yield prediction accuracy using different ML algorithms. by Gourab Saha (8987405)

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Multiple machine learning methods for screening heart failure related diagnostic biomarkers. by Ming Du (532508)

Global and local feature (predictor variable) explanations from the XGBoost trained with Quebec data (2014–2021). by Hamid Ghanbari (6821096)

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Pearson correlations among the candidate predictor variables, calculated at surveillance sites using a 1 000-m radius buffer. by Hamid Ghanbari (6821096)

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Performance of ML models for estimating tick population establishment at Quebec surveillance sites from 2022-2023, using predictor variables calculated at the surveillance sites us... by Hamid Ghanbari (6821096)

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Candidate predictor variables included in the initial parameter selection. by Hamid Ghanbari (6821096)

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Geographic distribution of surveillance sites and environmental context. A) Distribution of tick surveillance sites across Quebec (2014-2023) and Ontario (2015-2018), B) land cover... by Hamid Ghanbari (6821096)

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Workflow for estimating the probability of established tick populations. by Hamid Ghanbari (6821096)

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List of predictor variables included in the final models, calculated at the surveillance sites using a 1 000-meter radius buffer. by Hamid Ghanbari (6821096)

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XGBoost model output for 2022 at 250 m resolution. by Hamid Ghanbari (6821096)

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