applyCut

Implements the Classification-based on
Association Rules (CBA) algorithm for association rule classification.
The package, also described in Hahsler et al. (2019) <doi:10.32614/RJ-2019-048>,
contains several convenience methods that allow to automatically
set CBA parameters (minimum confidence, minimum support) and it also natively
handles numeric attributes by integrating a pre-discretization step.
The rule generation phase is handled by the 'arules' package.
To further decrease the size of the CBA models produced by the 'arc' package, postprocessing by the
'qCBA' package is suggested.

Tomas Kliegr

Association Rule Classification

applyCut function

<dl><dt>col</dt>
<dd>input vector with data.</dd>
<dt>cuts</dt>
<dd>vector with cutpoints.
There are several special values defined:
<code>NULL</code> indicates that no discretization will be performed, but the value will be converted to factor
 <code>"All"</code> indicates all values will be merged into one.</dd>
<dt>infinite_bounds</dt>
<dd>a logical indicating how the bounds on the extremes should look like.
If set to <code>FALSE</code>, the leftmost/rightmost intervals will be bounded by the minimum and maximum in the respective column.
If set to <code>TRUE</code>, the leftmost/rightmost intervals will be bounded by negative and positive infinity.</dd>
<dt>labels</dt>
<dd>a logical indicating whether the bins of the discretized data should be represented by integer codes or as interval notation using (a;b] when set to TRUE.</dd></dl>

Arguments

Apply Cut Points to Vector — applyCut

<dl>

<dt>col</dt>
<dd>input vector with data.</dd>


<dt>cuts</dt>
<dd>vector with cutpoints.
There are several special values defined:
<code>NULL</code> indicates that no discretization will be performed, but the value will be converted to factor
 <code>"All"</code> indicates all values will be merged into one.</dd>


<dt>infinite_bounds</dt>
<dd>a logical indicating how the bounds on the extremes should look like.
If set to <code>FALSE</code>, the leftmost/rightmost intervals will be bounded by the minimum and maximum in the respective column.
If set to <code>TRUE</code>, the leftmost/rightmost intervals will be bounded by negative and positive infinity.</dd>


<dt>labels</dt>
<dd>a logical indicating whether the bins of the discretized data should be represented by integer codes or as interval notation using (a;b] when set to TRUE.</dd>

</dl>

applyCut: Apply Cut Points to Vector

Description

Usage

Value

Arguments

See Also

Examples