Feature engineering#

ForePaaS enables you to fully specify which variables to select for your model.

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#Add a value-to-predict

The value you want to predict (i.e. the label) is saved in the Y dataset. To add a value-to-predict, click on Add a source next to Y.

Choose the source based on the input type you specified when generating your dataset and save.

#When the input type is Tables

You will be able to select one attribute from the training table.

#When the input type is Pictures from buckets

You will be able to select one or several folders from the training bucket.

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#Add features

The features, or variables, that are used to make a prediction are saved in the X dataset. To add features to your structured data model, click on Add a source next to X.

Choose as many variables as you want from the source based on the input type you specified when generating your dataset and save.

Shortcut tip: you have the option to add all variables in one go: this will add all the variables from the source except the one you chose as the value-to-predict.

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#Pre-processing

Advanced feature engineering should be carried out in the Data Processing Engine (DPE) on your source itself.

#Go further

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