Models overview
The Models page is where you create, train, test, and version machine-learning models.
Clarity supports four model types:
- Classification assigns one class to each pixel.
- Unmixing estimates a continuous response for each class in each pixel.
- Target Detection scores pixels for one selected target class.
- Regression predicts continuous values for the dataset's numeric label attributes.
See Model types for requirements and output differences.
Model details
Select a model to open its details drawer. The Overview tab contains the model metadata, dataset and band settings, training controls, and metrics. Test Predictions contains predictions generated from held-out test data.
Some managed or administrator accounts also see Compare and Deployments. These tabs are not available to every user.
Each model can have multiple versions. A version can be:
- a draft whose settings can still be edited;
- training or generating test results;
- trained and ready for compatible inference; or
- deprecated and no longer offered for new inference.