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

Data&Codes.rar by anonymous author (20478659)

Scatter diagram of different principal elements. by Jizhong Wang (7441697)

All Code and MoCap data for Cutaneous Rectilinear Algorithm tests by Henry Astley (22155685)

Data and code used in this article. by Yazhen Zhu (3595430)

Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…The Boruta technique was implemented to identify the important predictors of undernutrition, and logistic regression, artificial neural network, random forest, and extreme gradient boosting (XGB) were adopted to predict undernutrition (stunting, wasting, and underweight) risk. …”

Data & code. by Mingming Li (502877)

Research data and code file by shuo zhang (21176735)

Data Sheet 1_Semantic composition of robotic solver algorithms on graph structures.pdf by Sven Schneider (1366548)

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. …”

Optimal Channel Encoding/Decoding Algorithm Design with MATLAB by Saraf Mohaimen Chowdhury (21977243)

Boxplots of Shapley values for attributes preselected by Boruta method in a subsample of 600 instances. by Gilson Yuuji Shimizu (19837946)

Boxplots of LIME effects for attributes preselected by Boruta method in a subsample of 600 instances. by Gilson Yuuji Shimizu (19837946)

Code and data - WST 895 thesis by Hoosain Ebrahim (14058588)

ATF-DF-WA Algorithm Experimental Code by jinhao zhong (20616116)

“…<p dir="ltr">The provided code files serve the following purposes:</p><ul><li><b>Preprocess.py</b> – This script handles text preprocessing tasks, such as cleaning and preparing raw text data for further processing.…”

Calculation algorithm implementing the proposed model. by Landry Djopkop Kouanang (17131748)