Base Classifier

A base classifier is a foundational machine learning model used as a building block in more complex systems or to establish a baseline performance level. Current research focuses on improving base classifier performance through techniques like cost-sensitive learning (addressing class imbalances) and integrating them with other models, such as graph neural networks or Hidden Markov Models, to leverage contextual information and enhance accuracy. These advancements are significant for various applications, including fraud detection, improving the trustworthiness of AI systems through explainability methods, and refining probabilistic regression models for more accurate predictions and uncertainty quantification.