Data Type

Data types are fundamental to data science, impacting model accuracy, interpretability, and efficiency across diverse applications. Current research focuses on developing novel data types optimized for specific tasks, such as efficient quantization for machine learning models (e.g., using arbitrary bit precision) and handling mixed data types (numeric and non-numeric) for improved model explainability. These advancements are crucial for improving the performance and applicability of machine learning algorithms in various fields, including healthcare, cybersecurity (steganalysis), and building management, while also addressing privacy concerns through techniques like differential privacy.