7.8. Model evaluationΒΆ

evaluation.init_out_dict

Initiates the main model evaluatoin dictionary for a range of model metric scores.

evaluation.fill_out_dict

Appends the computed metric score per run to the main output dictionary.

evaluation.init_out_df

Initiates and empty main output dataframe.

evaluation.fill_out_df

Appends output dataframe of each simulation to main output dataframe.

evaluation.evaluate_prediction

Computes a range of model evaluation metrics and appends the resulting scores to a dictionary.

evaluation.polygon_model_accuracy

Determines a range of model accuracy values for each polygon.

evaluation.init_out_ROC_curve

Initiates empty lists for range of variables needed to plot ROC-curve per simulation.

evaluation.save_out_ROC_curve

Saves data needed to plot mean ROC and standard deviation to csv-files.

evaluation.calc_correlation_matrix

Computes the correlation matrix for a dataframe.

evaluation.get_feature_importance

Determines relative importance of each feature (i.e.

evaluation.get_permutation_importance

Returns a dataframe with the mean permutation importance of the features used to train a RF tree model.