qcbaIris2: Use the Iris dataset to test the experimental multi-rule QCBA...
In qCBA: Postprocessing of Rule Classification Models Learnt on Quantized Data
qcbaIris2 R Documentation
Use the Iris dataset to test the experimental multi-rule QCBA workflow.
Description
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
Usage
qcbaIris2()
Value
Accuracy.
qCBA documentation built on April 12, 2025, 1:59 a.m.
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| qcbaIris2 | R Documentation |
Use the Iris dataset to test the experimental multi-rule QCBA workflow.
Description
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
Usage
qcbaIris2()
Value
Accuracy.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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