Features.importances(target_num: int = 0, sort: bool = True) → Tuple[numpy.ndarray[Any, numpy.dtype[numpy.str_]], numpy.ndarray[Any, numpy.dtype[numpy.float64]]][source]

Returns the data for the feature importances, as displayed in the getML monitor.

target_num (int):

Indicates for which target you want to view the importances. (Pipelines can have more than one target.)

sort (bool):

Whether you want the results to be sorted.

(numpy.ndarray, numpy.ndarray):
  • The first array contains the names of the features.

  • The second array contains their importances. By definition, all importances add up to 1.