src.eval.rand_forest_evaluation

Classes

RandForestEvaluation(**kwargs)

class src.eval.rand_forest_evaluation.RandForestEvaluation(**kwargs)
Author:

Alberto M. Esmoris Pena

Class representing the result of evaluating a trained random forest. See RandForestEvaluator.

Variables:

  • problem_name – See Evaluator

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

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

  • permutation_importance_mean (np.ndarray) – The normalized mean permutation importance of each feature in [0, 1].

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

  • trees (list) – The list of trees representing the estimators of the random forest.

__init__(**kwargs)

Initialize/instantiate a RandForestEvaluation.

Parameters:

kwargs – The attributes for the RandForestEvaluation.

report(**kwargs)

Transform the RandForestEvaluation into a RandForestReport.

See RandForestReport.

Returns:

The RandForestReport representing the RandForestEvaluation.

Return type:

RandForestReport

can_report()

See Evaluation and evaluation.Evaluation.can_report().

plot(**kwargs)

Transform the RandForestEvaluation into a RandForestPlot.

See RandForestPlot.

Keyword Arguments:

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

  • show (bool) – Boolean flag to handle whether to show the plot (True) or not (False).

Returns:

The RandForestPlot representing the RandForestEvaluation.

Return type:

RandForestPlot

can_plot()

See Evaluation and evaluation.Evaluation.can_plot().