Key Features of AutoML | teradataml - Key Features 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

Key features of teradataml AutoML:

  • Supports different problem types:
    • Regression
    • Binary Classification
    • Multiclass Classification
  • Provides five different models for training based on problem types:
    • GLM
    • SVM
    • Decision Forest
      AutoML decision forest model is supported only when working from Windows platform. Support for Mac and Linux will be added in future.
    • XGBoost
    • KNN
  • Gives flexibility to select specific models out of available models.​
  • Performs all five phases in automated way, but can also be customized based on user input.
  • Generates model leaderboard and leader for given dataset.​
  • Provides prediction on validation dataset as well as user passed data using model leader or any other model from leaderboard.​
  • Provides early stopping criteria to stop AutoML training before completion time using two different options:
    • Defining early stopping timer
    • Defining early stopping metric threshold
  • Provides three different logging levels to display required contents, higher level provides more detailed output.