Permutation Feature Importance

Experiment initialization and data preparation

from piml import Experiment
from piml.models import XGB2Regressor

exp = Experiment()
exp.data_loader(data="BikeSharing", silent=True)
exp.data_summary(feature_exclude=["yr", "mnth", "temp"], silent=True)
exp.data_prepare(target="cnt", task_type="regression", silent=True)

Train Model

exp.model_train(model=XGB2Regressor(), name="XGB2")

PFI Plot

exp.model_explain(model="XGB2", show="pfi", n_repeats=10, figsize=(5, 4))
Permutation Feature Importance

Total running time of the script: ( 0 minutes 17.928 seconds)

Estimated memory usage: 21 MB

Gallery generated by Sphinx-Gallery