MLJAR AutoML

Train AutoML in Python

Train a full machine learning pipeline on tabular data. You don't have to apply any preprocessing on data, the AutoML will fill missing values and convert categorical, text and dates into numeric format if needed. The AutoML will perform algorithm search and tunning. Please select training mode that you would like to use and set the training time budget.

Available modes:

  • Explain - it is perfect for initial data analysis, very fast,
  • Perform - good for bulding production-level pipelines, considers prediction time during optimization,
  • Compete - the best model performance, it is using feature generation techniques and Stacked Ensemble.

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Interactive recipe

You can use below interactive recipe to generate code. This recipe is available in MLJAR Studio.

In the below recipe, we assume that you have following variables available in your notebook:

  • X (type DataFrame)
  • y (type Series)

Code explanation

  1. Create AutoML object. AutoML configuration is setup in the constructor.
  2. Train AutoML object.
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MLJAR AutoML