# Classification models ## Classification models in DAM Machine learning models, particularly classification models, play a crucial role in digital asset management. Classification models are algorithms that learn patterns and relationships in data to assign predefined categories or labels to new, unseen data. They can be used to categorize and organize assets, such as images, videos, or documents, based on their content or characteristics. Classification models are typically trained on labeled datasets, where each data instance is associated with a known category or label. During the training process, the model learns to recognize patterns and features in the input data that differentiate one category from another. Once trained, the model can classify new, unseen data based on the learned patterns. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.scaleflex.com/visual-ai/visual-ai/images/classification-models.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.