Recursive Feature Eliminator#
Recursive Feature Eliminator (RFE) is a supervised feature selector that uses the importance scores returned by a learner implementing the RanksFeatures interface to recursively drop feature columns with the lowest importance until a terminating condition is met.
Note: The default feature ranking base learner is a fully-grown decision tree.
Data Type Compatibility: Depends on the base learner
|1||min features||int||The minimum number of features to select from the dataset.|
|2||max dropped features||3||int||The maximum number of features to drop from the dataset per iteration.|
|3||max dropped importance||0.2||float||The maximum importance to drop from the dataset per iteration.|
|4||estimator||Auto||RanksFeatures||The base feature ranking learner instance.|
Return the final importances of the selected feature columns:
public importances() : ?array
use Rubix\ML\Transformers\RecursiveFeatureEliminator; use Rubix\ML\Classifiers\RandomForest; $transformer = new RecursiveFeatureEliminator(30, 2, 0.05 new RandomForest());
- I. Guyon et al. (2002). Gene Selection for Cancer Classification using Support Vector Machines.