predict.CBA: Model Prediction for Classifiers Based on Association Rules

In arulesCBA: Classification Based on Association Rules

Model Prediction for Classifiers Based on Association Rules

Description

Predicts classes for new data using a CBA classifier.

Usage

## S3 method for class 'CBA'
predict(object, newdata, type = c("class", "score"), ...)

accuracy(pred, true)

Arguments

object	An object of class CBA.
newdata	A data.frame or arules::transactions containing rows of new entries to be classified.
type	Predict "class" labels. Some classifiers can also return "scores".
...	Additional arguments are ignored.
pred, true	two factors with the same level representing the predictions and the ground truth (e.g., obtained with response()).

Value

A factor vector with the classification result.

Author(s)

Michael Hahsler

Examples

data("iris")

train_id <- sample(seq_len(nrow(iris)), 130)
iris_train <- iris[train_id, ]
iris_test <- iris[-train_id, ]

cl <- CBA(Species ~., iris_train)
pr <- predict(cl, iris_test)
pr

accuracy(pr, response(Species ~., iris_test))

arulesCBA documentation built on May 29, 2024, 11:49 a.m.