Base learner parameters. حسب Jingru Dong (14076094)

"…A risk prediction model was constructed based on four algorithms: Random Forest, XGBoost, Logistic Regression, and SVM. …"

Data inclusion and exclusion process. حسب Jingru Dong (14076094)

"…A risk prediction model was constructed based on four algorithms: Random Forest, XGBoost, Logistic Regression, and SVM. …"

S1 Data - حسب Jingru Dong (14076094)

"…A risk prediction model was constructed based on four algorithms: Random Forest, XGBoost, Logistic Regression, and SVM. …"

Experimental Sensor Data from Vehicles for Dynamic Vehicle Models حسب János Kontos (20463344)

"…</p><p><br></p><p dir="ltr">The data is stored in Apache Parquet format that can be processed via Pandas library in Python.</p><p><br></p><p dir="ltr">For more information please check our article:</p><p dir="ltr">Sensitivity Analysis of Long Short-Term Memory-based Neural Network Model for Vehicle Yaw Rate Prediction @MPDI Sensors</p>…"

Map of cumulative daily root-mean-square errors for each province in China in the test set. حسب Xiaoyi Wang (90589)

Table 1_Magnetic resonance imaging-based deep learning for predicting subtypes of glioma.docx حسب Zhen Yang (107412)

"…The receiver operating characteristic curve (ROC), area under the curve (AUC) of the ROC were generated in the jupyter notebook tool using python language to evaluate the accuracy of the models in classification and comparing the predictive value of different MRI sequences.…"

Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models حسب Pascal Kündig (19824557)

"…<p>Latent Gaussian process (GP) models are flexible probabilistic nonparametric function models. …"

Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i> حسب Hao Chen (20313552)

"…The repository contains all necessary data and code for reproducing the analyses of beetle breeding phenology predictions using circadian activity patterns.…"

GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios حسب Yang Lan (20927512)

"…</p><p dir="ltr">All data are stored in GeoTIFF (.tif) format and can be accessed and processed using ArcGIS, ENVI, R, and Python. Each GeoTIFF file contains grid-based predictions of habitat suitability, with values ranging from 0 to 1. …"

Horuss Research: methodology for validating unstructured data using large language models حسب Fabiano Castello (6803171)

"…<p dir="ltr">The methodology involves structuring unstructured client data, like medical records, using Large Language Models (LLMs) to generate reliable insights. First, data is collected via RPA tools like Python/Selenium. …"

DRLiPS: A Novel Method for Prediction of Druggable RNA-Small Molecule Binding Pockets Using Machine Learning حسب Sowmya Ramaswamy Krishnan (20867198)

Supplementary Material for: The prediction of hematoma growth in acute intracerebral hemorrhage: from 2-dimensional shape to 3-dimensional morphology حسب figshare admin karger (2628495)

"…Amongst all prediction models, the PCM presented the highest predictive value for active bleeding. …"

Dataset for the Modeling and Bibliometric Analysis of Business plan for Entrepreneurship حسب Shofie Galuh Amanda (22121604)

"…</p><p dir="ltr">The dataset provides significant value for researchers, practitioners, and policymakers by presenting structured bibliometric evidence alongside predictive modeling of future research trajectories in entrepreneurial business planning. …"

Data Sheet 1_Predicting the prognosis of patients with sudden sensorineural hearing loss by analyzing the audiometric curve of the unaffected ear.zip حسب Xuan Sun (619836)

Image 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.tif حسب Xuehui Fan (10762662)

"…This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.…"

A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification حسب Mohammed Nasser Al-Andoli (21431681)

Dataset for the Modeling and Bibliometric Analysis of E-business in Entrepreneurship (1997–2024) حسب Aggie Moses Zeuse (21460466)

"…These include a summary of Main Information (PNG), a graph of the Annual Scientific Production (PNG), a Thematic Map (PNG) illustrating core research themes, and an analysis of Trend Topics (PNG). For the modeling component, a predictive analysis was conducted using Python to forecast future publication volumes. …"

Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.…"

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx حسب Xuehui Fan (10762662)

"…This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.…"

Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx حسب Xuehui Fan (10762662)

"…This study aims to analyze the treatment preferences of outpatient rehabilitation patients by using data and a grading tool to establish predictive models. The goal is to improve patient visit efficiency and optimize resource allocation through these predictive models.…"