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h2otraining-dataamazon-sagemakerautoml

How to hyperparametrize Amazon SageMaker Training Jobs Console

I'm trying to use de AWS SageMaker Training Jobs console to train a model with H2o.AutoMl.

I got stuck trying to set up Hyperparameters, specifically setting up the 'training' field.

{'classification': true, 'categorical_columns':'', 'target': 'label'}

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I'm trying to set up a classification training job (1/0), and I believe that everything else on the setup page I can cope, but I don't know how to set up the 'training' field. My data is stored on S3 as a CSV file, as the algorithm requires.

My data has around 250000 columns, 4 out of them are categorical, one of them is the target, and the remainder is continuous variables (800 MB)

target column name = 'y'
categorical columns name = 'SIT','HOL','CTH','YTT'

I hope someone could help me.

Thank you!

Solution

  • After I asked I came across an explanation from SageMaker examples.

    {classification': 'true', 'categorical_columns': 'SIT','HOL','CTH','YTT','target': 'y'}.

    Problem solved!