Description Usage Arguments Value Examples
CPAR_C Associative Classification Algorithm from KEEL.
1 | CPAR_C(train, test, delta, min_gain, alpha, rules_prediction)
|
train |
Train dataset as a data.frame object |
test |
Test dataset as a data.frame object |
delta |
delta. Default value = 0.05 |
min_gain |
min_gain. Default value = 0.7 |
alpha |
alpha. Default value = 0.66 |
rules_prediction |
rules_prediction. Default value = 5 |
A data.frame with the actual and predicted classes for both train
and test
datasets.
1 2 3 4 5 6 7 8 9 10 | #data <- loadKeelDataset("breast")
#Create algorithm
#algorithm <- RKEEL::CPAR_C(data, data)
#Run algorithm
#algorithm$run()
#See results
#algorithm$testPredictions
|
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