To facilitate the key features mentioned in the previous section, teradataml AutoML provides the following methods:
- _init_(): Create instance for AutoML training.Three different APIs are available for instance creation based on problem types:
- AutoML (AutoML._init_): Generic AutoML API that can be used to solve all three supported problem type.
- AutoRegressor (AutoRegressor._init_): Specific AutoML API to solve regression problem type.
- AutoClassifier (AutoClassifier._init_): Specific AutoML API to solve classification problem type.
The following methods are common to all these three APIs. - fit: Fit over given dataset during AutoML training.
- leaderboard: Display model leaderboard containing model rank and corresponding performance metrics.
- leader: Display best performing model.
- model_hyperparameters: Get hyperparameters of the model based on rank in leaderboard.
- predict: Generate prediction and performance metrics.
- evaluate: Evaluate on data using model rank in leaderboard to generate performance metrics.
- generate_custom_config: Generate custom config JSON required for customized run.
- deploy: Save models to the specified table.
- load: Load models information from the specified table.
- remove_saved_models: Remove the specified table containing saved models.