src.eval.rand_forestpp_evaluation

Classes

RandForestPPEvaluation(**kwargs)

class src.eval.rand_forestpp_evaluation.RandForestPPEvaluation(**kwargs)
Author:

Alberto M. Esmoris Pena

Class representing the result of evaluating a trained C++ random forest. See RandForestPPEvaluator.

Variables:

  • problem_name – See Evaluator

  • fnames (list or tuple) – The name for each feature.

  • importance (np.ndarray) – The normalized MDI importance of each feature in [0, 1], summing to 1.0.

  • permutation_importance_mean (np.ndarray) – The mean permutation importance of each feature.

  • permutation_importance_stdev (np.ndarray) – The standard deviation of the permutation importance of each feature.

__init__(**kwargs)

Initialize/instantiate a RandForestPPEvaluation.

Parameters:

kwargs – The attributes for the RandForestPPEvaluation.

report(**kwargs)

Transform the RandForestPPEvaluation into a RandForestPPReport.

See RandForestPPReport.

Returns:

The RandForestPPReport.

Return type:

RandForestPPReport

can_report()

See Evaluation and evaluation.Evaluation.can_report().

plot(**kwargs)

Transform the RandForestPPEvaluation into a RandForestPPPlot.

Since the C++ backend does not expose individual tree structures, the plot shows feature importance bar charts instead of tree diagrams.

See RandForestPPPlot.

Keyword Arguments:

  • path (str) – The path to store the plot.

  • show (bool) – Boolean flag for showing the plot (True) or not (False).

Returns:

The RandForestPPPlot.

Return type:

RandForestPPPlot

can_plot()

See Evaluation and evaluation.Evaluation.can_plot().