saveTree

Generate a residual tree on a subset of the data specified by the factor level mainfaclev (main factor level)

Finds features through a detailed analysis of model residuals using rpart classification and regression trees. Scans the residuals of a model across subsets of the data to identify areas where the model differs from the actual data.

Richard Davis

featurefinder

Feature Finder

saveTree function

<dl><dt>data</dt>
<dd>A dataframe containing the residual and some predictors</dd>
<dt>vars</dt>
<dd>A list of candidate predictors</dd>
<dt>expr</dt>
<dd>A expression to be modelled by the RPART tree</dd>
<dt>i</dt>
<dd>An integer corresponding to the factor level</dd>
<dt>varname</dt>
<dd>A string corresponding to the name of the factor variable being analysed</dd>
<dt>mainfaclev</dt>
<dd>A level of the mainfac factor</dd>
<dt>treeGenerationMinBucket</dt>
<dd>Minimum size for tree generation</dd>
<dt>...</dt>
<dd>and parameters to be passed through</dd></dl>

Arguments

saveTree — saveTree

<dl>

<dt>data</dt>
<dd>A dataframe containing the residual and some predictors</dd>


<dt>vars</dt>
<dd>A list of candidate predictors</dd>


<dt>expr</dt>
<dd>A expression to be modelled by the RPART tree</dd>


<dt>i</dt>
<dd>An integer corresponding to the factor level</dd>


<dt>varname</dt>
<dd>A string corresponding to the name of the factor variable being analysed</dd>


<dt>mainfaclev</dt>
<dd>A level of the mainfac factor</dd>


<dt>treeGenerationMinBucket</dt>
<dd>Minimum size for tree generation</dd>


<dt>...</dt>
<dd>and parameters to be passed through</dd>

</dl>

saveTree: saveTree

Description

Usage

Value

Arguments