qcbaIris2

<p>Learns a CBA classifier, and then transforms it  to a multirule classifier,
 including rule annotation and fuzzification. Applies the learnt model with rule mixture classification.
The model  is saved to a temporary file.
This function uses a package-specific seed option, which can be overridden 
with `options(qcba.seed = 42)`, where 42 is an example seed value</p>

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

qcbaIris2: Use the Iris dataset to test the experimental multi-rule QCBA workflow.

Description

Usage

Arguments

Value