A number of further amendments to the plot_ensemble_oob.py example
script were suggested in the PR thread and addressed accordingly:
- The ExtraTreesClassifier models were removed from the example, since
they don't use bootstrapping by default (but can be using bootstrap=True).
- Included the OOB errors for RandomForestClassifier models with various
max_features values.
- Changed the sample datasets to make for a nicer looking plot.
- Changed "cross-validated" to "validated" in the docstring.
- Added the relevant page numbers to the Hastie et al. reference.
- PEP8 compliance, fixed line > 80 chars.
@amueller provided feedback on improving my original PR (#4665) of the
plot_ensemble_oob.py script.
A number of major changes were made accordingly:
- Used `matplotlib.pyplot` instead of `pylab`.
- To improve the run-time to <10secs, I reduced the dimensionality of
the sample dataset and set the max. number of estimators to 150.
- To avoid OOB warnings, the min. number of estimators was set to 15.
Values <15 would still raise the warnings.
- The script is PEP8-compliant via the `pep8` command-line script. I
needed to move `print(__doc__)` and author list comments.
- Re-added @amueller to the author list (had mistakenly been removed).
- Added a link to this example to the user-guide under the `Ensemble
Methods` section.
Shota