Prototype models

Prototype models are a way in machine learning where the system classifies data by comparing it to a set of known examples or "prototypes" for each category. Think of it like having a reference image for each category and seeing which reference your new data most closely resembles. When a new input arrives, the model measures how similar it is to each prototype and assigns it to the closest one. This approach allows for straightforward, intuitive classification, especially useful when the data's structure can be effectively summarized by these prototypes.