add_noise

Given a distribution name with a scale and loc parameters, the step optionally applies another scaling to it either based on the standard deviation of the column or a proportionally to each point through the relative parameter in order to preserve the underlying structure of the data. Then the computation is carried as follows:

new value = original value + relative scaling factor * random sample from the distribution.

If this relative parameter is not given or is set to abs, then the relative scaling factor is 1.

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Usage

The following examples show how the step can be used in a recipe.

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Inputs & Outputs

The following are the inputs expected by the step and the outputs it produces. These are generally columns (ds.first_name), datasets (ds or ds[["first_name", "last_name"]]) or models (referenced by name e.g. "churn-clf").

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Configuration

The following parameters can be used to configure the behaviour of the step by including them in a json object as the last “input” to the step, i.e. step(..., {"param": "value", ...}) -> (output).