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

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

Types of machine learning algorithms. by 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.…”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …”

Data Sheet 2_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.zip by Rui Zhang (13940)

“…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. …”

Data Sheet 1_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.docx by Rui Zhang (13940)

“…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. …”

Comparison of the EODA algorithm with existing algorithms in terms of recall. by Sunil Kumar (102321)

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Comparison of the EODA algorithm with existing algorithms in terms of precision. by Sunil Kumar (102321)

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Results of RF algorithm screening factors. by Jintao Li (448681)

Performance of different machine learning algorithms. by Apichat Suratanee (634281)

Comparison of the EODA algorithm with existing algorithms in terms of F1-Score. by Sunil Kumar (102321)

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Comparative performance evaluation of 3Mont with other feature selection algorithms over 10 iterations. by Miray Unlu Yazici (14792680)

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Performance of machine learning algorithms. by Wenxue Liu (6877754)

Parameters of the machine learning algorithms used in the study. by Xiaoyan Yang (259084)

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The proposed algorithm of the outlier detection method. by Sunil Kumar (102321)

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Supporting data for “Developing algorithms to optimize recommender system for self-regulated learning promotion in online contexts: a design-based study” by Long Zhang (11129139)

Performance evaluation measure of the machine learning algorithm after data balancing with SMOTE and grid search tuning. by Alemu Birara Zemariam (17540938)

“…<p>Performance evaluation measure of the machine learning algorithm after data balancing with SMOTE and grid search tuning.…”

Data Sheet 1_Development and validation of an endoscopic diagnostic model for sessile serrated lesions based on machine learning algorithms.docx by Xinying Yu (16400811)

“…</p>Conclusion<p>This study represents the first application of an ML algorithm techniques to the endoscopic classification of serrated polyps. …”