Intro

ecosystem.Ai uses a worker architecture to define and run predictions. The base configurations are stored in the ecosystem_meta database across many collections.

Key Features

• Meta-Data Driven: All predictor configuration items are managed from the model meta-data.
• Broad Range of Parameters: Parameters are model dependent and can be set in the model meta-data.
• Many Model Types: Multiple model types are supported, including regression, classification, and clustering.
• Model Result: The model result is stored in the models database.
• Easy Testing of Models: Models can be tested using the Test Model option.
• Deploy: Models are saved in the models database and can be deployed for predictions.