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 14 of 14 for “"Shapley Additive Explanations (shap)"”.
-
Explainable Deep Learning Approach for Detecting Money Laundering Transactions in Banking System
… and explaining the predictions using SHapley Additive exPlanations (SHAP) XAI method. The results showed that the CNN model outperformed other models, indicating better handling of compliance risk. On the contrary, CNN model showed higher number of false positives compared to other …
-
A Multitask Deep Learning Framework for Clinical Decision-Making in Assisted Reproductive Technology
… baselines. To enhance clinical trust, we apply SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME), which consistently uncover biologically meaningful variables, including biomarkers such as Anti-Müllerian Hormone (AMH), patient age, and the day-3 …
-
Revamping Manufacturing Systems: Utilization of Data Driven Models, Interpretable Machine Learning, and Data-Product Stakeholder Flow Analysis
… learning models in the Semiconductor Fab. The SHapley Additive exPlanations (SHAP) methodology was applied to generate beeswarm and bar plots for the SHAP results, which identified the most important features to improve the throughput prediction. The study showed that Machine E utilization has …
-
Three Essays on Corporate Governance and CEO Dismissal
… across multiple performance dimensions. Using SHapley Additive exPlanations (SHAP) values, the study decomposes model predictions to reveal the relative importance of firm-specific factors, where market-based performance metrics contribute materially to dismissal likelihood. Long-short …
-
Machine Learning Methods for Churn Prediction and Infrastructure Resilience
… future infrastructure vulnerabilities. Employing SHapley Additive exPlanations (SHAP), I interpret model predictions, highlighting critical factors such as precipitation, windspeed, and atmospheric pressure. Additionally, I propose frameworks for quantifying financial impacts of future outages and …
-
Adaptive systems for DDoS attacks detection and mitigation in IoT networks
… evolution for resource efficiency. The SHAP-Based Explanation and Lightweight DDoS Attack Detection (SHIELD) system uses SHapley Additive exPlanations (SHAP) for interpretability of individual predictions. The final objective addresses adaptive mitigation through a Game-Theoretic DDoS …
-
The Role of Explainable Artificial Intelligence in Data Science [Il Ruolo dell'Intelligenza Artificiale Esplicabile nella Scienza dei Dati]
… Local Interpretable Model-agnostic Explanations (LIME) e SHapley Additive exPlanations (SHAP), dimostrando la versatilità insita nelle metodologie di interpretabilità. Come primo passo, applichiamo questi approcci interpretativi per estrarre caratteristiche fondamentali dai dati …
-
Convolutional Neural Networks for Robust Fynbos Leaf Classification: Enabling Trustworthy Machine Learning in Botanical Science
… model. The model evaluation process makes use of SHapley Additive exPlanations (SHAP), a tool for visualising model predictions, to contribute to the explian-ability of the model and to develop trust and confidence in machine-learning algorithms, with the ultimate aim of providing a tool to merge …
-
A novel approach by integrating physically and Machine leaning-based models for landslide susceptibility assessment
… of ML methods (i.e., black box nature) using SHapley Additive exPlanations (SHAP) algorithm. The proposed method was tested at Chukha, Bhutan (area of 1,879.5 km²), a frequent landslide-prone area in the Himalayan region. As the first objective, the study develops a novel model based on …
-
Intelligent Pricing Systems for Hotels: From Prediction to Optimization [Sistema di prezzi intelligente per hotel: dalla previsione all'ottimizzazione]
… Spiegabile (XAI). In particolare, gli SHapley Additive ExPlanations (SHAP) vengono utilizzati per fornire spiegazioni chiare e accessibili delle previsioni del modello, sia a livello globale che locale. Inoltre, la tesi presenta l'architettura dell'intero sistema, mostrando come la …
-
Using Machine Learning and the Water Evaluation and Planning model to Evaluate Climate Change Impacts on Surface Water Allocation in the Upper Awash Sub-Basin, Ethiopia
… Memory (LSTM) network (MAE: 0.41 vs. 0.46). SHapley Additive exPlanations (SHAP) analysis identified lagged population growth and unmet demand as the most influential predictors, alongside temperature and drought-related variables. To support adaptive water governance, a Non-Dominated Sorting …
-
Analysis of Association Between Demographic, Socioeconomic, and Built Environment Factors and Pedestrian Safety Using Traditional and AI Approaches
… of machine learning models, specifically SHapley Additive exPlanations (SHAP), in explaining how these factors affect Equivalent Property Damage Only (EPDO) rates. The findings reveal that auto-oriented network density is consistently associated with higher pedestrian crash risks, while …
-
ESSAYS ON BANKING MERGERS AND ACQUISITIONS
… methodology. Beyond that, this paper explores SHapley Additive exPlanations (SHAP) analysis to interpret how bank features influence these two types of risk events from XGBoost method. The results show that XGBoost method gives better prediction accuracy if both developing the model and …
-
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