infer_gender
Try to infer a person’s gender given a first name.
Uses a machine learning model trained on a large database of names and the frequencies of associated genders.
Usage
The following examples show how the step can be used in a recipe.
To use the default labels “male” and “female” in the resulting output simply use
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").
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).
Labels for the male and female categories. An object mapping the “male” and “female” categories to custom labels.
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