Data and code resources. by Sam Hall-McMaster (10343795)

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

“…We identified the important features related to IA using the Boruta algorithm. Predictions were made using different machine learning (ML) (decision tree (DT), random forest (RF), support vector machines (SVMs), and logistic regression (LR)) models. …”

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)

“…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. …”

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

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Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

Variable selection procedure using the Boruta algorithm. by Qiudie Liu (22655907)

“…<p>Variable selection procedure using the Boruta algorithm.</p>…”

Feature selection using the Boruta algorithm method. by Alemu Birara Zemariam (17540938)

Participant selection algorithm. by Alex Gough (16734033)

Participant selection algorithm. by Alex Gough (16734033)

The selection algorithm flowchart. by Shiyu Wang (813972)

GA pseudo-code. by Jianpeng Zhang (528185)

“…GA is used to optimize the feature selection process to identify the key feature subsets that have the greatest impact on model performance. …”

Pseudo-code for the study design model. by Jianpeng Zhang (528185)

“…GA is used to optimize the feature selection process to identify the key feature subsets that have the greatest impact on model performance. …”

Patient selection algorithm. by Dwi Kisworo Setyowireni (22656144)

Proposed genetic algorithm for feature selection. by Shirin Dehghan (19837936)

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Feature selection results from the Boruta algorithm. by Junying Wei (1710550)

Subjects:

TIR-Learner v3: New generation TE annotation program for identifying TIRs by Tianyu Lu (18856792)

“…The old TIR suffers from slow execution on large genomes due to intense I/O operations and less efficient algorithms, it also lacks maintainability due to legacy dependency issues. …”

Steps involved in genetic algorithm for feature selection. by Mohd Sakib (20565228)

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Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived from the 3-level wavelet transform (WT) at four resolutions. These features were used as inputs for traditional ML algorithms. The left map demonstrates the correlation matrix of 52 features crafted from 4 resolutions of the 3-level WT, which are used as inputs for traditional ML algorithms.... by Quang Dung Dinh (20995766)

“…These features were used as inputs for traditional ML algorithms. The left map demonstrates the correlation matrix of 52 features crafted from 4 resolutions of the 3-level WT, which are used as inputs for traditional ML algorithms. …”

Scenarios for algorithms using IEEE 33 bus. by Bachirou Bogno (20485724)