Substring

class getml.preprocessors.Substring(begin: int, length: int, unit: str = '')

Bases: _Preprocessor

The Substring preprocessor extracts substrings from categorical columns and unused string columns.

The preprocessor will be applied to all categorical and text columns that were assigned one of the subroles getml.data.subroles.include.substring or getml.data.subroles.only.substring.

To further limit the scope of a substring preprocessor, you can also assign a unit.

Args:

begin (int):

Index of the beginning of the substring (starting from 0).

length (int):

The length of the substring.

unit (str, optional):

The unit of all columns to which the proprocessor should be applied. These columns must also have the subrole substring.

If it is left empty, then the preprocessor will be applied to all columns with the subrole getml.data.subroles.include.substring or getml.data.subroles.only.substring.

Example:

my_df.set_subroles("col1", getml.data.subroles.include.substring)

my_df.set_subroles("col2", getml.data.subroles.include.substring)
my_df.set_unit("col2", "substr14")

# Will be applied to col1 and col2
substr13 = getml.preprocessors.Substring(0, 3)

# Will only be applied to col2
substr14 = getml.preprocessors.Substring(0, 3, "substr14")

pipe = getml.Pipeline(
    population=population_placeholder,
    peripheral=[order_placeholder, trans_placeholder],
    preprocessors=[substr13],
    feature_learners=[feature_learner_1, feature_learner_2],
    feature_selectors=feature_selector,
    predictors=predictor,
    share_selected_features=0.5
)

Attributes Summary

unit

Methods Summary

validate([params])

Checks both the types and the values of all instance variables and raises an exception if something is off.

Attributes Documentation

unit: str = ''

Methods Documentation

validate(params=None)

Checks both the types and the values of all instance variables and raises an exception if something is off.

Args:

params (dict, optional):

A dictionary containing the parameters to validate. If not is passed, the own parameters will be validated.