trim_frequencies
Remove values whose frequencies (counts) are above/below a given threshold.
Affected categories are replaced with the missing value (NaN).
Usage
The following examples show how the step can be used in a recipe.Examples
Examples
To remove categories ocurring fewer than 2 times in the column
cat_col: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").
Inputs
Inputs
A categorical column to trim.
Outputs
Outputs
A categorical column with fewer categories than the input.
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).
Parameters
Parameters
The number N indicating how many of the most common values to filter (in descending order).Values must be in the following range:
Values with a lower frequency (count) than this will be removed.Values must be in the following range:
Values with a higher frequency (count) than this will be removed.Values must be in the following range: