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

الموضوعات:

Features selection using the Boruta algorithm. حسب 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. 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)

"…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. …"

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

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

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

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

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

الموضوعات:

Participant selection algorithm. حسب Alex Gough (16734033)

Participant selection algorithm. حسب Alex Gough (16734033)

The selection algorithm flowchart. حسب Shiyu Wang (813972)

GA pseudo-code. حسب 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. حسب Dwi Kisworo Setyowireni (22656144)

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

الموضوعات:

List of the time used by each algorithm. حسب JiaMing Gong (20427837)

"…In this manner high quality and common samples are randomly selected for training the classifier. Finally, to solve the issue of concept drift, EDAC designs and implements an ensemble classifier that uses a self-feedback strategy to determine the initial weight of the classifier by adjusting the weight of the sub-classifier according to the performance on the arrived data chunks. …"

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

الموضوعات:

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

Scenarios for algorithms using IEEE 69 bus. حسب Bachirou Bogno (20485724)

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

الموضوعات:

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.... حسب 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. …"