cave.analyzer.feature_importance module

class cave.analyzer.feature_importance.FeatureImportance(runscontainer)[source]

Bases: cave.analyzer.base_analyzer.BaseAnalyzer

runscontainer: RunsContainer contains all important information about the configurator runs

classmethod check_for_bokeh(d)
feature_importance(pimp, output_dir)[source]
get_html(d=None, tooltip=None) → Tuple[str, str]

General reports in html-format, to be easily integrated in html-code. ALSO FOR BOKEH-OUTPUT.

Parameters

d (Dictionary) – a dictionary that will be later turned into a website

Returns

script, div – header and body part of html-code

Return type

str, str

get_jupyter()

Depending on analysis, this creates jupyter-notebook compatible output.

get_name()[source]
plot_bokeh()

This function needs to be called if bokeh-plots are to be displayed in notebook AND saved to webpage.