qCBA (version 0.3)

predict.qCBARuleModel: Aplies qCBARuleModel

Description

Applies qcba rule model on provided data. Automatically detects whether one-rule or multi-rule classification is used

Usage

# S3 method for qCBARuleModel
predict(object, newdata, testingType,
  loglevel = "WARNING", ...)

Arguments

object

qCBARuleModel class instance

newdata

data frame with data

testingType

either mixture for multi-rule classification or firstRule for one-rule classification. Applicable only when model is loaded from file.

loglevel

logger level from java.util.logging

...

other arguments (currently not used)

Value

vector with predictions.

See Also

qcba

Examples

# NOT RUN {
allData <- datasets::iris[sample(nrow(datasets::iris)),]
trainFold <- allData[1:100,]
testFold <- allData[101:nrow(datasets::iris),]
rmCBA <- cba(trainFold, classAtt="Species")
rmqCBA <- qcba(cbaRuleModel=rmCBA, datadf=trainFold)
print(rmqCBA@rules)
prediction <- predict(rmqCBA,testFold)
acc <- CBARuleModelAccuracy(prediction, testFold[[rmqCBA@classAtt]])
message(acc)

# }