Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 43 for “"Extreme Gradient Boosting"”.
-
Predição de mortalidade intra-hospitalar em pacientes com insuficiência cardíaca: extreme gradient boosting versus GWTG e ADHERE
… avaliar e comparar o desempenho preditivo do Extreme Gradient Boosting (XGB), um modelo de classificação usado em conjunto com um algoritmo de aprendizado de máquina, com dois escores tradicionais, ADHERE e GWTG, para risco de mortalidade em pacientes internados na UTI com IC. Materiais e …
-
Predicting Gentrification Patterns in London: A Machine Learning Approach to Analysing Deprivation and Urban Change Across Neighbourhoods
… three types of ML models (random forest, gradient boosting machine, and extreme gradient boosting), analyses their predictive performance against each other, and compares them to a traditional regression approach. The study aims to forecast gentrification in London in 2025. The findings …
-
Credit scorecards in retail banking: enhancing interpretability through shapley values and evaluating the effectiveness of alternative data for improved accuracy
… learning algorithms like random forest and eXtreme gradient boosting outperform traditional logistic regression in accuracy, their complex predictor variable representation hinders interpretability. To reconcile this, the study discretizes numerical variables, applies one-hot encoding, and …
-
Prediction of loss to follow-up in postpartum others living with HIV
… and several machine learning models.. An extreme gradient boosting model was developed and validated to predict the risk of loss to follow-up within the first 9 months postpartum based on routinely available patient data at the point of discharge after delivery. Model calibration was …
-
Coastal water level prediction: a comparative study of statistical and machine learning techniques for time series forecasting
… alongside machine learning methods including extreme gradient boosting, support vector machines, and long short-term memory networks. Extreme gradient boosting with 24-hour of lagged input features was found to have the greatest overall test accuracy and stable predictions over the 96-hour …
-
An exploration of alternative features in micro-finance loan default prediction models
… are logistic regression, random forests, extreme gradient boosting, and neural networks. Finally the paper identifies whether or not accurate loan default prediction models can be trained using only the alternative features developed throughout this minor dissertation. The results of the …
-
An Approach For Scalable First-Order Rule Learning On Twitter Data
… based on user interaction and incorporates a gradient boosting approach with a tool called BoostSRL for first-order rule mining. We show how this scalable solution on first order predicates is more accurate and efficient than existing systems, such as ProbKB (a scalable system to construct …
-
Miles Matter: Demographics, Distance, and Decision-Making
… learning-based (graph neural networks and extreme gradient boosting) analysis, I explore the multifaceted nature of decision-making processes in different urban environments. The hidden patterns revealed by artificial intelligence show that distance is the key determinant of mode choice, …
-
The Effect of Dataset Size on the Performance of Classification Algorithms for Credit Scoring
… regression, random forests, neural networks, gradient boosting machines, extreme gradient boosting, and stacked ensembles. This paper conducts two separate analyses on these datasets and algorithms – firstly, a general analysis, where algorithm performance is benchmarked by average relative …
-
Comparative analysis of Machine Learning Algorithms for Estimating Global Solar Radiation at Selected Weather Stations in Vhembe District Municipality
… (K-NN), Support Vector Ma chines(SVM) and Extreme Gradient Boosting mechanism(XGBoost)) is used to estimate the GRS in this study. The RF model on Mutale station was found to be the best fitting model with R² = 0.9902, MSE = 0.4085 and RMSE = 0.6391, followed by XGB with R² = 0.9898, MSE = …
-
PREDICTING METRICS FOR NAVAL SUPPLY SYSTEMS COMMAND WHOLESALE INVENTORY OPTIMIZATION MODEL
… approaches: k-nearest neighbors (KNN) and Extreme Gradient Boosting (XGBoost). Both methods train very fast for more than 21,000 items and multiple CIPs by item. These observations are divided into four categories, and the results demonstrate that XGBoost consistently outperforms KNN. …
-
Optimising credit card fraud detection through machine learning and deep learning with spatial-temporal imbalance handling
… Forest, CatBoost, Logistic Regression (LR), Extreme Gradient Boosting (XGBoost), AdaBoost, Gaussian Naive Bayes, and Extra Trees Classifier—and two deep learning models, Gated Recurrent Unit (GRU) and Neural Network (NN). Performance was evaluated using Recall, Precision, F1 Score, ROC-AUC …
-
A machine learning model for vehicle crash type prediction
… to the specific crash type. In this study, eXtreme Gradient Boosting (XGBoost) method is applied to predict the occurrence of different types of crashes. A two-layer model is proposed. The first layer is used to distinguish potential crashes from crash-free observations and the second layer …
-
Association of Fall-Related Injuries and Different Diagnoses in Older Adults of Ontario: A Machine Learning Approach
… algorithms: decision tree, random forest, and extreme gradient boosting tree (XGBoost). Secondary data from two Ontario health administrative databases (NACRS, DAD) covering the period 2006-2015 were analyzed. Older adults (aged ≥ 65 years) who sought treatment for FRIs in emergency departments …
-
Machine learning for high performance computing applications
… first application used K-means clustering and Gradient Boosted Tree Regression (GBTR) to predict estimated queue time for jobs submitted to an HPC system. This method achieved a 96% accuracy when predicting whether or not a job would start prior to a specified deadline. The second application …
-
Modelos de machine learning para el análisis de calidad del agua y su contribución para la agricultura
… (RF), artificial neural network (ANN) y xgboost (extreme gradient boosting)). Los modelos fueron evaluados mediante R2, MAE, MSE y RMSE, destacando el buen desempeño del Random Forest, Decision Tree, ANN para el análisis del OD con un R2 de 0,741, 0714 y 0,785 respectivamente; para el análisis de …
-
Analysis of bankruptcy prediction of shipping industry - Machine Learning Approach
… advanced machine learning models, including Extreme Gradient Boosting (XGBoost) and Long Short-Term Memory (LSTM) networks. A comprehensive literature review and interviews with industry practitioners were conducted to refine the variables used in the models. These models predict bankruptcy …
-
Forecasting Markers of Habitual Driving Behaviors Associated with Crash Risk
… most informative features out of them to feed an extreme gradient boosting machine learning algorithm. The model operates upon these select features in a time window covering the recent past to make short-term predictions for the immediate future, regarding the driver’s distraction and driving …
-
Machine Learning Applications in Blockchain for Renewable Energy Systems
… comparative analysis of ensemble methods such as eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Random Forest is conducted for residual demand. To optimize these models, the study contrasts bio-inspired Swarm Intelligence, Honey Badger Algorithm (HBA), …
Page 1 of 3