Features¶

class getml.pipeline.Features(name, targets)[source]¶

Custom class for handling the features generated by the pipeline.

Example:

names, importances = my_pipeline.features.importances()

names, correlations = my_pipeline.features.correlations()

sql_code = my_pipeline.features.to_sql()

Methods

`correlations`([target_num, sort])	Returns the data for the feature correlations, as displayed in the getML monitor.
`importances`([target_num, sort])	Returns the data for the feature importances, as displayed in the getML monitor.
`to_pandas`()	Returns all information related to the features in a pandas data frame.
`to_sql`([targets])	Returns SQL statements visualizing the features.