Essays about: "explainable predictions"
Showing result 1 - 5 of 23 essays containing the words explainable predictions.
-
1. Explainable AI by Training Introspection
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : Deep Neural Networks (DNNs) are known as black box algorithmsthat lack transparency and interpretability for humans. eXplainableArtificial Intelligence (XAI) is introduced to tackle this problem. MostXAI methods are utilized post-training, providing explanations of themodel to clarify its predictions and inner workings for human understanding. READ MORE
-
2. Explaining Mortality Prediction With Logistic Regression
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Explainability is a key component in building trust for computer calculated predictions when they are applied to areas with influence over individual people. This bachelor thesis project report focuses on the explanation regarding the decision making process of the machine learning method Logistic Regression when predicting mortality. READ MORE
-
3. Explainable Reinforcement Learning for Gameplay
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : State-of-the-art Machine Learning (ML) algorithms show impressive results for a myriad of applications. However, they operate as a sort of a black box: the decisions taken are not human-understandable. READ MORE
-
4. Increasing the Trustworthiness ofAI-based In-Vehicle IDS usingeXplainable AI
University essay from Mittuniversitetet/Institutionen för informationssystem och –teknologiAbstract : An in-vehicle intrusion detection system (IV-IDS) is one of the protection mechanisms used to detect cyber attacks on electric or autonomous vehicles where anomaly-based IDS solution have better potential at detecting the attacks especially zero-day attacks. Generally, the IV-IDS generate false alarms (falsely detecting normal data as attacks) because of the difficulty to differentiate between normal and attack data. READ MORE
-
5. Using XAI Tools to Detect Harmful Bias in ML Models
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : In the past decade, machine learning (ML) models have become farmore powerful, and are increasingly being used in many important contexts. At the same time, ML models have become more complex, and harder to understand on their own, which has necessitated an interesting explainable AI (XAI), a field concerned with ensuring that ML and other AI system can be understood by human users and practitioners. READ MORE
