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.
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Showing 1 to 20 of 124 for “"Gradient Boosting"”.
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Estimating End-User Throughput Using Service Provider Cell Traces Via Gradient Boosting
… traces, and consequently, we build a Regularized Gradient Boosting model to predict the user's throughput using traces that are exclusively collected from the service provider's resources. Our approach shows that using our imputing and prediction approaches, we can accurately estimate the user …
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Predição de mortalidade intra-hospitalar em pacientes com insuficiência cardíaca: extreme gradient boosting versus GWTG e ADHERE
… 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 métodos. A …
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Integrating Gradient Boosting and Generative Models: Hybrid Approach to Address Class Imbalance and Evaluation Gaps in Real-World Systems
… Using this framework, we benchmark LightGBM—a gradient boosting method known for its computational efficiency and predictive accuracy—on an imbalanced dataset, comparing its performance against standard academic evaluation criteria. Our results demonstrate that Tail-end FPR Max Recall fills …
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Prediction of moisture and protein in corn kernels from multiple origins based on NIR-PLSR with gradient boosting machines for feature selection
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01
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Breeding white storks in former East Prussia : comparing predicted relative occurrences across scales and time using a stochastic gradient boosting method (TreeNet), GIS and public data
In dieser Arbeit wurden verschiedene GIS-basierte Habitatmodelle für den Weißstorch (Ciconia ciconia) im Gebiet der ehemaligen deutschen Provinz Ostpreußen (ca. Gebiet der russischen Exklave Kaliningrad und der polnischen Woiwodschaft Ermland-Masuren) erstellt. Zur Charakterisierung der Beziehung …
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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 …
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Credit scorecards in retail banking: enhancing interpretability through shapley values and evaluating the effectiveness of alternative data for improved accuracy
… 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 employs …
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Variable selection in discrete survival models
… Shrinkage and Selection Operator (Lasso) and gradient boosting on discrete survival data. Parameter related mean squared errors (MSEs) and false positive rates suggest Lasso performs better than gradient boosting. Frailty models outperform discrete survival models that do not account for …
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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 …
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An affordance-inspired tool for automated web page labeling and classification
… and labeling web pages. This system uses a gradient boosting classifier from the scikit-learn Python package to identify which of four tasks may be performed on a given web page. It also attempts to automatically label the input fields and buttons on the web page using a gradient boosting …
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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 …
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Predicting smartphone email marketing campaign clicks with the LightGBM algorithm
… alussa esittelen mallinnuksessa käytettavan Gradient Boosting Decision Tree mallin seka siitä johdetun LightGBM mallin, jotka perustuvat päätöspuihin. Kerroen ensin lyhyesti päätöspuista, jonka jälkeen esittelen Gradient Boosting Decision Tree mallien teoreettisen taus- tan. Siirryn sen …
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Utilising machine learning techniques on simulated viral evolution datasets to improve viral recombinant identification
… several models, including logistic regression, gradient boosting, random forests and neural networks, on a dataset of 491 124 sequences. A novel neural network architecture employing position selection achieved the highest performance with a weighted Area Under Curve (AUC) of 0.784, surpassing …
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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 performed on …
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Coastal water level prediction: a comparative study of statistical and machine learning techniques for time series forecasting
… 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 forecast …
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Artificial intelligence in business analytics, capturing value with machine learning applications in financial services
… as Generalized Linear Models, Random Forest, Gradient Boosting, and Artificial Neural Networks were tested, compared, and combined to test their predictive strength and robustness in different scenarios and use cases. The results indicate the superiority of Gradient Boosting when it comes to …
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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 research …
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Machine Learning Applications in Blockchain for Renewable Energy Systems
… 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), Particle Swarm …
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