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 10 of 10 for “"Agnostic Explanations"”.

  1. ULIME: Uniformly weighted Local Interpretable Model-agnostic Explanations for Image Classifiers

    … proposed interpretability methods to generate explanations for the behavior of machine learning models. One popular interpretability method is Local Interpretable Model-agnostic Explanations (LIME), which can explain any black-box model trained on any type of data. Although LIME is a powerful …

    queens Repository record for ULIME: Uniformly weighted Local Interpretable Model-agnostic Explanations for Image Classifiers (opens in a new tab)

  2. Inductive logic programming with gradient descent for supervised binary classification

    … In contrast to Local Interpretable Model-Agnostic Explanations (LIME), this thesis seeks to develop an interpretable model using logical rules, rather than explaining existing blackbox models. We extend recent inductive logic programming methods developed by Evans and Grefenstette [3] to …

    mit Repository record for Inductive logic programming with gradient descent for supervised binary classification (opens in a new tab)

  3. Multi-scale local explanation approach for image analysis using model-agnostic explainable artificial intelligence (XAI)

    … of their decisions. Local Interpretable Model-agnostic Explanations (LIME) is an explanation method which produces a coarse heatmap as a visual explanation highlighting the most important superpixels affecting the CNN’s decision. This thesis aims to explore and develop a multi-scale scheme of …

    uoit Repository record for Multi-scale local explanation approach for image analysis using model-agnostic explainable artificial intelligence (XAI) (opens in a new tab)

  4. A Multitask Deep Learning Framework for Clinical Decision-Making in Assisted Reproductive Technology

    … 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 high-quality embryo …

    mit Repository record for A Multitask Deep Learning Framework for Clinical Decision-Making in Assisted Reproductive Technology (opens in a new tab)

  5. Supporting Human Performance with Post-hoc Explanations in Automated Decision Assistance

    … promote appropriate reliance behaviors. Post-hoc explanations have emerged as a strategy to support appropriate reliance on automated decision aids based on machine learning. However, existing methods to generate post-hoc explanations often fail to demonstrate systematic effectiveness in aiding …

    toronto-retro Repository record for Supporting Human Performance with Post-hoc Explanations in Automated Decision Assistance (opens in a new tab)

  6. STUDYING PRODUCT REVIEWS USING SENTIMENT ANALYSIS BASED ON INTERPRETABLE MACHINE LEARNING

    … reviews, we employ Local Interpretable Model- Agnostic Explanations (LIME) to explain the impact of words in reviews on the decisions of the classification models. Noting that different models can give similar predictions, which is a phenomenon known as the Rashomon Effect, our work provides …

    maryland Repository record for STUDYING PRODUCT REVIEWS USING SENTIMENT ANALYSIS BASED ON INTERPRETABLE MACHINE LEARNING (opens in a new tab)

  7. The Role of Explainable Artificial Intelligence in Data Science [Il Ruolo dell'Intelligenza Artificiale Esplicabile nella Scienza dei Dati]

    … delle caratteristiche, 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 …

    catania Repository record for The Role of Explainable Artificial Intelligence in Data Science [Il Ruolo dell'Intelligenza Artificiale Esplicabile nella Scienza dei Dati] (opens in a new tab)

  8. Causal and system-theoretic approaches to interpretable machine learning

    … on the widely used Local Interpretable Model-Agnostic Explanations (LIME), we adapt this technique for the time series setting and demonstrate how it can be extended through tools from causal inference to reveal cause-effect relationships among input and output variables. We next consider …

    umn Repository record for Causal and system-theoretic approaches to interpretable machine learning (opens in a new tab)

  9. Learning based algorithms for temperature control and fouling prediction in heat-exchangers

    … we confirm using locally interpretable model agnostic explanations around randomly selected operating points.

    uiuc Repository record for Learning based algorithms for temperature control and fouling prediction in heat-exchangers (opens in a new tab)

  10. AI-based leakage prediction with uncertainty quantification and explainable AI for nuclear system

    Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01

    uiuc Repository record for AI-based leakage prediction with uncertainty quantification and explainable AI for nuclear system (opens in a new tab)