customCBARuleModel-class

customCBARuleModel

This class represents a rule-based classifier, where rules are represented as string vectors in a data frame

Implements the Quantitative Classification-based on
Association Rules (QCBA) algorithm (<doi:10.1007/s10489-022-04370-x>).
QCBA postprocesses rule classification models making them typically smaller and in some cases more accurate.
Supported are 'CBA' implementations from 'rCBA', 'arulesCBA' and 'arc' packages, and 'CPAR', 'CMAR', 'FOIL2' and 'PRM' implementations
from 'arulesCBA' package and 'SBRL' implementation from the 'sbrl' package. The result of the post-processing is an ordered CBA-like rule list.

Tomas Kliegr

qCBA

Postprocessing of Rule Classification Models Learnt on Quantized
Data

Tomáš Kliegr

customCBARuleModel-class function

<dl>
<dt><code>rules</code></dt>
<dd>dataframe with rules</dd></dl>
<dt><code>cutp</code></dt>
<dd>list of cutpoints</dd>
<dt><code>classAtt</code></dt>
<dd>name of the target class attribute</dd>
<dt><code>attTypes</code></dt>
<dd>attribute types</dd>

Slots

customCBARuleModel — customCBARuleModel-class

<dl>
<dt><code>rules</code></dt>
<dd>dataframe with rules</dd>


<dt><code>cutp</code></dt>
<dd>list of cutpoints</dd>


<dt><code>classAtt</code></dt>
<dd>name of the target class attribute</dd>


<dt><code>attTypes</code></dt>
<dd>attribute types</dd>


</dl>

customCBARuleModel-class: customCBARuleModel

Description

Arguments

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