Local Explainability
Introduction Local explainability refers to the ability to understand and interpret the decisions made by a machine learning model at an individual instance level. It aims to provide insights into… Local Explainability
Introduction Local explainability refers to the ability to understand and interpret the decisions made by a machine learning model at an individual instance level. It aims to provide insights into… Local Explainability
Introduction An operating point, also known as a bias point or quiescent point, refers to the steady-state condition of an electronic circuit or system. It represents the specific values of… Operating Point
Introduction A Generative Adversarial Network (GAN) is a type of machine learning model that consists of two neural networks: a generator and a discriminator. The generator network is responsible for… Generative Adversarial Network (GAN)
Introduction General explainability refers to the ability of a system or model to provide understandable and interpretable explanations for its decisions or actions. It is an important aspect of artificial… General Explainability
Introduction Multimodal Artificial Intelligence (AI) refers to the integration of multiple modes of communication and perception, such as speech, text, images, and gestures, into AI systems. By combining these different… Multimodal Artificial Intelligence
Introduction The Foundation Model (FM) is a state-of-the-art language model developed by OpenAI. It is designed to generate human-like text and has been trained on a vast amount of internet… Foundation Model (FM)
Introduction Training data is a crucial component in the development of artificial intelligence systems. It refers to the information or examples that are used to train an AI model or… Training Data
Introduction Introduction: In the context of binary classification, a true negative refers to a situation where a model correctly predicts the absence of a particular condition or event when it… True Negative
Introduction Explainability (XAI) refers to the ability of an AI system to provide understandable and transparent explanations for its decisions or actions. It aims to bridge the gap between the… Explainability (XAI)
Introduction Feature selection is a crucial step in machine learning and data analysis. It involves selecting a subset of relevant features from a larger set of available features to improve… Feature Selection