MuniNone

MuniNone is a term used in machine learning, particularly in models that classify or analyze data with multiple possible categories. It indicates the absence of a specific class or category label—meaning the model has determined that none of the predefined options apply to the data point. Essentially, MuniNone signals that the input does not fit into any of the recognized categories, allowing the system to handle uncertain or out-of-scope data effectively. It helps improve the accuracy and flexibility of classification models by explicitly acknowledging when data doesn't match expected classes.