Infer gender¶
inference • model
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 are the step's expected inputs and outputs and their specific types.
infer_gender(first_name: category, {
"param": value
}) -> (gender: sex)
where the object {"param": value} is optional in most cases and if present may contain any of the parameters described in the
corresponding section below.
Example¶
To use the default labels "male" and "female" in the resulting output simply use
infer_gender(ds.first_name) -> (ds.gender)
More examples
To use labels "M" and "F" instead
infer_gender(ds.first_name), "labels": {"male": "M", "female": "F"}) -> (ds.gender)
Inputs¶
first_name: column:category
Column containing first names.
Outputs¶
gender: column:sex
Predicted gender for each name.
Parameters¶
labels: object
Labels for the male and female categories. An object mapping the "male" and "female" categories to custom labels.
Items in labels
male: string = "male"
Label for the "male" category.
female: string = "female"
Label for the "female" category.