Explainability describes a model’s ability to return information describing how a model produced a given prediction, inference, or result. The details returned depend on the explainable input type. Modzy currently supports many types of explanability, but provides a graphical UI for image classification and text classification models. For this feature to work, models must include explainability code within the model container itself before it's deployed to Modzy. This is commonly called "White Box" Explainability.
These models return JSON outputs with mask values for explainable results. Mask values include the prediction results and the explainability results (pixel values that motivate the prediction made by the model).
Updated 12 months ago