Features selection using the Boruta algorithm. حسب Nishat Tasnim Thity (21755858)

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Recommended network representation formats for different types of biological networks. Each biological network type exhibits unique topological characteristics that make certain re... حسب Giuseppe Agapito (104634)

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

"…Feature selection was performed using the Boruta algorithm and model performance was evaluated by comparing accuracy, precision, recall, F1 score, MCC, Cohen’s Kappa and AUROC.…"

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

"…</p><p>Results</p><p>Our study included 2,213 patients, of whom 345 (15.6%) experienced in-hospital mortality. The Boruta algorithm identified 29 significant risk factors, and the top 13 variables were used for developing machine learning models. …"

Data. حسب Nishat Tasnim Thity (21755858)

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Heuristic approaches for configuring network alignment algorithms. حسب Giuseppe Agapito (104634)

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The workflow of Algorithm 2 with the example in حسب Badhan Das (7434362)

Parameters of ML algorithms. حسب Md. Maeen Molla (20827041)

Comparison of preprocessing methods for network alignment. حسب Giuseppe Agapito (104634)

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Key aspects of network alignment documentation. حسب Giuseppe Agapito (104634)

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Features identified through LASSO analyses and Boruta. حسب Lang Gao (12963876)

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Comparison of local and global network alignment approaches. حسب Giuseppe Agapito (104634)

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Data Sheet 3_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 2_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 4_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 6_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.docx حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 1_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.pdf حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Top 2^nd tree from the fitted RF model to predict multi-levels of IA. حسب Nishat Tasnim Thity (21755858)

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The ROC curves to predict multi-classes of IA among university students in Bangladesh using ML models. حسب Nishat Tasnim Thity (21755858)

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Prevalence of IA by severity. حسب Nishat Tasnim Thity (21755858)

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