Forward Selection is a generic method to obtain a subset of parameters to achieve the same prediction error as with the full parameter set. Each parameter is scored by how much the out-of-bag-error of an empirical performance model based on a random forest is decreased.
Calculate parameter-importance using the PIMP-package.
General reports in html-format, to be easily integrated in html-code. ALSO FOR BOKEH-OUTPUT.
d (Dictionary) – a dictionary that will be later turned into a website
script, div – header and body part of html-code
- Return type
Depending on analysis, this creates jupyter-notebook compatible output.
- modus: str
modus for parameter importance, from [forward-selection, ablation, fanova, lpi]
This function needs to be called if bokeh-plots are to be displayed in notebook AND saved to webpage.