CBA_helpers | R Documentation |
Helper functions to extract the response from transactions or rules, determine the class frequency, majority class, transaction coverage and the uncovered examples per class.
classes(formula, x) response(formula, x) classFrequency(formula, x, type = "relative") majorityClass(formula, transactions) transactionCoverage(transactions, rules) uncoveredClassExamples(formula, transactions, rules) uncoveredMajorityClass(formula, transactions, rules)
formula |
A symbolic description of the model to be fitted. |
x, transactions |
An object of class arules::transactions or rules. |
type |
|
rules |
A set of rules. |
response
returns the response label as a factor.
classFrequency
returns the item frequency for each class label as a
vector.
majorityClass
returns the most frequent class label in the
transactions.
Michael Hahsler
itemFrequency()
, rules, arules::transactions.
data("iris") iris.disc <- discretizeDF.supervised(Species ~ ., iris) iris.trans <- as(iris.disc, "transactions") inspect(head(iris.trans, n = 3)) # convert the class items back to a class label response(Species ~ ., head(iris.trans, n = 3)) # Class labels classes(Species ~ ., iris.trans) # Class distribution. The iris dataset is perfectly balanced. classFrequency(Species ~ ., iris.trans) # Majority class # (Note: since all class frequencies for iris are the same, the first one is returned) majorityClass(Species ~ ., iris.trans) # Use for CARs cars <- mineCARs(Species ~ ., iris.trans, parameter = list(support = 0.3)) #' # Class labels classes(Species ~ ., cars) # Number of rules for each class classFrequency(Species ~ ., cars, type = "absolute") # conclusion (item in the RHS) of the rule as a class label response(Species ~ ., cars) # How many rules (using the first three rules) cover each transactions? transactionCoverage(iris.trans, cars[1:3]) # Number of transactions per class not covered by the first three rules uncoveredClassExamples(Species ~ ., iris.trans, cars[1:3]) # Majority class of the uncovered examples uncoveredMajorityClass(Species ~ ., iris.trans, cars[1:3])
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