Comparison of different optimization algorithms. حسب Hang Zhao (143592)

الموضوعات: "…crayfish optimization algorithm…"

ML algorithms in cyber security. حسب Abdullah Asım Yılmaz (20715311)

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

الموضوعات:

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

الموضوعات:

Boruta’s algorithm ranks the importance of potential risk factors for in-hospital mortality. حسب Sheng Chen (21971)

The run time for each algorithm in seconds. حسب Edward Antonian (21453161)

"…These methods are tested on both real and synthetic data, with the former taken from a network of air quality monitoring stations across California. …"

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

الموضوعات:

Algorithm process. حسب Wei Cui (92129)

Deep attention network architecture for arrhythmia classification. حسب Hang Zhao (143592)

الموضوعات: "…crayfish optimization algorithm…"

Table 1_Association between the stress hyperglycemia ratio and all-cause mortality in patients with hemorrhagic stroke: a retrospective analysis based on MIMIC-IV database.docx حسب Wei Zhu (23646)

The Search process of the genetic algorithm. حسب Wenguang Li (6528113)

الموضوعات:

The construction process of the FCM clustering algorithm. حسب Xini Fang (20861990)

الموضوعات:

Processed results from ECG data with the P-T algorithm. حسب Daehyun Kwon (11985629)

Multi-sensor fusion process and algorithm workflow. حسب Hongliang Zou (20707270)

Video 1_A hybrid elastic-hyperelastic approach for simulating soft tactile sensors.mp4 حسب Berith Atemoztli De la Cruz Sánchez (21758708)

"…A significant challenge for simulating tactile sensors is balancing the trade-off between accuracy and processing time in simulation algorithms and models. …"

Types of machine learning algorithms. حسب 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. …"

Computational Domain: The computational domain was discretized using conformal tetrahedral elements, resulting in a total of 926K elements. حسب Martina Bukač (20161460)

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. …"