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class-rebalancing

Description

Note

More information about the service specification can be found in the Core concepts > Service documentation.

This service uses rebalances a dataset based on a target class, it combines oversampling (SMOTE) and undersampling (ENN) to be more generalizable. In order for the service to work your dataset label column must be called "target". Finally, avoid having multiple empty lines at the end of the file.

The API documentation is automatically generated by FastAPI using the OpenAPI standard. A user friendly interface provided by Swagger is available under the /docs route, where the endpoints of the service are described.

This simple service only has one route /compute that takes an image as input, which will be used to find the average shade color in the image.

Environment variables

Check the Core concepts > Service > Environment variables documentation for more details.

Run the tests with Python

Check the Core concepts > Service > Run the tests with Python documentation for more details.

Start the service locally

Check the Core concepts > Service > Start the service locally documentation for more details.