center.preds

Given the specified 'center.at' values of the Interpreter object, this
 function centers all of the plots in the Interpreter object
 of the specified type of plot.

Provides several methods for model distillation and interpretability
for general black box machine learning models and treatment effect estimation
methods. For details on the algorithms implemented, see <https://forestry-labs.github.io/distillML/index.html>
Brian Cho, Theo F. Saarinen, Jasjeet S. Sekhon, Simon Walter.

Theo Saarinen

distillML

Model Distillation and Interpretability Methods for Machine
Learning Models

Brian Cho

Jasjeet Sekhon

Simon Walter

center.preds function

<dl><dt>object</dt>
<dd>The Interpreter object to use</dd>
<dt>features</dt>
<dd>A vector of names for the 1-D features we want to center</dd>
<dt>plot.type</dt>
<dd>The type of plot that the user wants to center the predictions of.
should be one of either "ICE", "PDP.1D", or "PDP.2D"</dd>
<dt>feats.2d</dt>
<dd>A 2-column dataframe or matrix that gives the first variable in
in the first column, and the second variable in the next. The
number of rows is equal to the number of 2-D PDPs one would like
to center.</dd></dl>

Arguments

Centers the predicted values for 1-d ICE and PDP plots or 2-d PDP plots — center.preds

<dl>

<dt>object</dt>
<dd>The Interpreter object to use</dd>


<dt>features</dt>
<dd>A vector of names for the 1-D features we want to center</dd>


<dt>plot.type</dt>
<dd>The type of plot that the user wants to center the predictions of.
should be one of either "ICE", "PDP.1D", or "PDP.2D"</dd>


<dt>feats.2d</dt>
<dd>A 2-column dataframe or matrix that gives the first variable in
in the first column, and the second variable in the next. The
number of rows is equal to the number of 2-D PDPs one would like
to center.</dd>

</dl>

center.preds: Centers the predicted values for 1-d ICE and PDP plots or 2-d PDP plots

Description

Usage

Value

Arguments

Details