pctCorrect

For classification models, calculate the percent of 
 individuals correctly classified in a specified percent of trees in 
 the forest.

Estimate significance of importance metrics
for a Random Forest model by permuting the response
variable. Produces null distribution of importance
metrics for each predictor variable and p-value of
observed. Provides summary and visualization functions for 'randomForest'
results.

Eric Archer

rfPermute

Estimate Permutation p-Values for Random Forest Importance
Metrics

pctCorrect function

<dl><dt>x</dt>
<dd>a <code>rfPermte</code> or <code>randomForest</code> model object.</dd>
<dt>pct</dt>
<dd>vector of minimum percent of trees voting for each class. Can be 
<code>0:1</code> or <code>0:100</code>.</dd></dl>

Arguments

Eric Archer <a href="/link/eric.archer%40noaa.gov?package=rfPermute&version=2.5.2" data-mini-rdoc="rfPermute::eric.archer@noaa.gov">eric.archer@noaa.gov</a>

Author

Percent Correctly Classified — pctCorrect

<dl>

<dt>x</dt>
<dd>a <code>rfPermte</code> or <code>randomForest</code> model object.</dd>


<dt>pct</dt>
<dd>vector of minimum percent of trees voting for each class. Can be 
<code>0:1</code> or <code>0:100</code>.</dd>

</dl>

Eric Archer <a href='mailto:eric.archer@noaa.gov'>eric.archer@noaa.gov</a>

pctCorrect: Percent Correctly Classified

Description

Usage

Value

Arguments

Author

Examples