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

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Feature selection using Boruta algorithm. by 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. by 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. …”

G R code algorithm. by R. Sakthivel (2589547)

“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”

Code used for data analysis in this study. by Nourin Sultana (22339463)

“…This study applies and evaluates machine learning (ML) algorithms to predict LBW and identify its key risk factors in Bangladesh. …”

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

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Code and data. by Shangyang Jin (21772466)

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

The method for determining the chemical constituents of unknown materials in the algorithm. by Dong Hyeok Choi (12562048)

Code. by Shamsuz Zoha (22339469)

“…This study aimed to identify the determinants of C-section delivery and develop an ML-based predictive model using data from the Bangladesh Demographic and Health Survey (BDHS) 2022. …”

Maple code for algorithm 3. by Peter Thompson (165468)

Data Sheet 3_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip by 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 by 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 by 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 by 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 by 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. …”

code&data by Liyuan Liu (18298084)

The metro zone algorithm pseudo-code. by Sarah Alhumoud (22258183)

Data and code. by Hao Cao (2248066)

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

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