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 16 of 16 for “"Shapley values"”.
-
Computational Methods for Estimating Global Sensitivity Indices and Shapley Values
… global sensitivity measures (DGSM), and Shapley values. The dissertation introduces two new control variate Monte Carlo estimators based on the truncated sparse polynomial chaos expansion of the function in hand. The control variate estimators are used to estimate the lower and upper …
-
Appley: Approximate Shapley Values for Model Explainability in Linear Time
… A coalition game theoretic approach called Shapley Value provides a fair way to tackle the challenge. However, the growth of computation time of the exact Shapley Values is exponential in the number of variables. Hence, it is common to use approximations as opposed to the exact Shapley …
-
Credit scorecards in retail banking: enhancing interpretability through shapley values and evaluating the effectiveness of alternative data for improved accuracy
… variables, applies one-hot encoding, and employs Shapley values to derive interpretable credit scores for random forest, eXtreme gradient boosting, light gradient boosting machine, and categorical boosting models. This approach produces credit scorecards that align with industry standards. …
-
Causal and system-theoretic approaches to interpretable machine learning
… input and output variables. We next consider Shapley values, another prominent XAI method that has demonstrated the ability to generate coherent explanations across different types of data, including time series data. We find that the computation of Shapley values has striking similarities to …
-
k-Label Dependent Evolutionary Distance Weighting for Software Defect Prediction
… (MCC) as the fitness function. In addition, Shapley values are used to explain the importance of software features in defect predictions to provide insights into the interpretability of the model. The $k$-LDEDW model is then compared with graph neural networks (GNN), clustering techniques, …
-
Data-Centric Machine Learning for Speech and Audio
… recognition, we develop a method for estimating Shapley values of speech data for training an end-to-end neural ASR model, which performs a structured prediction task. We also demonstrate how data valuation can be used for environmental sound classification. In the context of ecoacoustic …
-
Why Are Some Watersheds More Sediment-Productive Than Others? An Explainable AI Approach
… in the estimation of SY and SDR, yielding R2 values of 0.59 and 0.60, respectively. Model interpretation using Shapley values revealed that anthropogenic factors—including urban area, pasture area, and road density—exert stronger controls on SDR than natural drivers such as slope or …
-
Machine Learning for Causal Estimation
… into popular attribution frameworks such as Shapley values, which then inherit its statistical guarantees. Simulation studies confirm the excellent performance of our method, and we demonstrate its utility through an applied case study. The third chapter tackles a common challenge in applied …
-
Efficient and Faithful Algorithms for Interpretable Machine Learning
… data modeled by MLPs, we focus on accelerating Shapley value computation, a widely used method rooted in cooperative game theory. While Shapley values provide theoretically sound feature attributions, their computation is NP-hard due to the exponential number of input coalitions. To address …
-
Canaries in the coal mine: Boosted machine learning for the classification of recessions in the eurozone business cycle
… gradient boosting framework. Using quarterly GDP values for all of the EA19 (with the exception of Ireland due to data availability), business cycle data was produced using the Bry-Boschan algorithm, coupled with seasonal and calendar smoothing via Eurostat. In order to identify the nations which …
-
Data Driven Synthesis Planning Applied to Zeolite Materials
… and interprets the model results through Shapley values to determine impacts of specific hydrothermal synthesis variables. Using multi-fidelity data and Bayesian inference, zeolite crystallization curves are studied to determine nucleation and crystal growth behavior. Both of these tasks …
-
Informing decision-making in single-objective, mixed-variable design problems
… (PFI, also known as Mean Decrease Accuracy), and Shapley values. These existing workflows are applied to varying sample sizes of three different datasets related to the application to low-carbon structural design. The same samples are evaluated using the hybrid technique previously proposed by the …
-
USE OF ON-FARM DATA AND MILK LEUCOCYTE COMPONENTS FOR MONITORING THE HEALTH OF DAIRY COWS
… stage of lactation, and farm. The highest values of neutrophils (>60% of TLC) were found at the beginning and at the end of lactation, the two most critical moments for mastitis onset. In accordance, high level of neutrophils (>63% of TLC) was described as one of the risk factors of high …
-
Game Theoretic and Analytical Approaches to International Cooperation and Investment Problems
… and hence to have a nonempty core with the Shapley value allocations belonging to the core. A compensation scheme is devised based on the Shapley value allocations, whereby participants who enjoy a greater payoff with respect to the technological cooperation compensate the participants who …
-
Resource Allocation on Networks: Nested Event Tree Optimization, Network Interdiction, and Game Theoretic Methods
… two marginal cost-induced methods; and a Shapley value approach. We also provide a game-theoretic insight into the existing procedure for apportioning railcars to railroads, and develop an alternative railroad allocation scheme based on capital plus operating costs. Extensive computational …
-
From big data to personal narratives: a supervised learning framework for decoding the course of traumatic brain injury in intensive care
… is estimated with a temporal extension of the SHapley Additive exPlanations (TimeSHAP) algorithm. The first endpoint of my supervised learning framework is functional outcome at six months according to the Glasgow Outcome Scale – Extended (GOSE). For ordinal GOSE prediction, expanding the …