print.EBM

Display basic information about a fitted ebm object.

An interface to the 'Python' 'InterpretML' framework for fitting explainable boosting machines (EBMs); see Nori et al. (2019) <doi:10.48550/arXiv.1909.09223> for details. EBMs are a modern type of generalized additive model that use tree-based, cyclic gradient boosting with automatic interaction detection. They are often as accurate as state-of-the-art blackbox models while remaining completely interpretable.

Brandon Greenwell

Explainable Boosting Machines

print.EBM function

<dl><dt>x</dt>
<dd>A fitted ebm object.</dd>
<dt>digits</dt>
<dd>The number of significant digits to be passed to <code><a href="/link/format()?package=ebm&version=0.1.0" data-mini-rdoc="ebm::format()">format()</a></code>
when <a href="/link/print?package=ebm&version=0.1.0" data-mini-rdoc="ebm::print">print</a>ing.</dd>
<dt>...</dt>
<dd>Additional optional arguments to be passed to <code><a href="/link/print.default()?package=ebm&version=0.1.0" data-mini-rdoc="ebm::print.default()">print.default()</a></code>.</dd></dl>

Arguments

Print model summary — print.EBM

<dl>

<dt>x</dt>
<dd>A fitted ebm object.</dd>


<dt>digits</dt>
<dd>The number of significant digits to be passed to <code><a href='https://rdrr.io/r/base/format.html'>format()</a></code>
when <a href='https://rdrr.io/r/base/print.html'>print</a>ing.</dd>


<dt>...</dt>
<dd>Additional optional arguments to be passed to <code><a href='https://rdrr.io/r/base/print.default.html'>print.default()</a></code>.</dd>

</dl>

print.EBM: Print model summary

Description

Usage

Value

Arguments