Methods of AutoML | teradataml - Methods of AutoML - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
March 2024
Language
English (United States)
Last Update
2024-04-09
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Product Category
Teradata Vantage

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.​
  • predict: Generate prediction and performance metrics.​
  • generate_custom_config: Generate custom config JSON required for customized run.