Percentage of Missing Data from PNC Dataset. حسب Daniel Niguse Mamo (16813898)

"…The study employs machine learning techniques to analyse secondary data from the 2016 Ethiopian Demographic and Health Survey. It aims to predict postnatal care utilization and identify key predictors via Python software, applying fifteen machine-learning algorithms to a sample of 7,193 women. …"

Top 10 features influencing PNC utilization. حسب Daniel Niguse Mamo (16813898)

"…The study employs machine learning techniques to analyse secondary data from the 2016 Ethiopian Demographic and Health Survey. It aims to predict postnatal care utilization and identify key predictors via Python software, applying fifteen machine-learning algorithms to a sample of 7,193 women. …"

Settings for ABC-SMC code. حسب Román Zapién-Campos (9592478)

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. …"

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.</p><p dir="ltr">The dataset includes:</p><ol><li>Raw locomotor activity measurements (.txt files) with 1-minute resolution</li><li>Breeding experiment data (Pair_breeding.csv) documenting nest IDs, population sources, photoperiod treatments, and breeding success</li><li>Activity measurement metadata (Loc_metadataset.csv) containing detailed experimental parameters and daily activity metrics extracted using tsfresh</li></ol><p dir="ltr">The repository also includes complete analysis pipelines implemented in both Python (3.8.8) and R (4.3.1), featuring:</p><ul><li>Data preprocessing and machine learning model development</li><li>Statistical analyses</li><li>Visualization scripts for generating Shapley plots, activity pattern plots, and other figures</li></ul><p></p>…"

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

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

"…The analysis and visualization were carried out using R Biblioshiny for thematic mapping and trend topics, and Microsoft Excel for main information and annual publication production. For modeling, Python was applied to generate projection analyses of annual scientific production using polynomial regression. …"

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. …"

Cathode carbon block material parameters [14]. حسب Chenglong Gong (20629836)

"…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …"

Sodium concentration distribution cloud map. حسب Chenglong Gong (20629836)

"…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …"

Sodium binding coefficient R. حسب Chenglong Gong (20629836)

"…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …"

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)

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>…"

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 and analysis codes for coarse-grained simulations of metal-organic cages حسب Emma Wolpert (21223817)

"…<p dir="ltr">The dataset relates to the study <i>“The role of shape and interaction directionality in the crystalline phase behaviour of octahedral metal–organic cages,” w</i>hich<i> </i>introduces a computational framework that combines semi-empirical dimer calculations with coarse-grained modelling to predict how octahedral metal-organic cages crystallise. …"

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.…"

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. …"

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. …"

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.…"