[英]R: overwrite rules that apriori produced
I want to overwrite confidence values of an apriori output, then put the output into is.redundant. 我想覆盖先验输出的置信度值,然后将输出放入is.redundant。 I got an error at the last line. 我在最后一行出现错误。 How do you do it? 你怎么做呢?
library(arules)
data(Groceries) # read sample data
# find apriori rules
outApriori = apriori(Groceries,
parameter = list(support=0.001, confidence=0.70, minlen=1, maxlen=4)
,appearance = list(rhs = "whole milk" ) )
dfApriori = as.data.frame(inspect(outApriori[1:5])) # convert into data.frame
# modify the confidence value conservatively by adding one error sample
(estimateConfidence= dfApriori$count / (1 + round( dfApriori$count / dfApriori$confidence ) ))
dfApriori$confidence = estimateConfidence
outRmRedundant <- dfApriori[!is.redundant(dfApriori)] # Error in (function (classes, fdef, mtable) :
# Error in (function (classes, fdef, mtable) :
# unable to find an inherited method for function ‘is.redundant’ for signature ‘"data.frame"’
The function is.redundant()
expects a rules
object not a data.frame
. 函数is.redundant()
需要一个rules
对象,而不是data.frame
。 Here is how you change the quality slot of the rules
object: 这是更改rules
对象的质量位置的方法:
library(arules)
data(Groceries)
# find apriori rules
rules <- apriori(Groceries,
parameter = list(support=0.001, confidence=0.70, minlen=1, maxlen=4),
appearance = list(rhs = "whole milk"))
estimatedConfidence <- quality(rules)$count / (1 + round(quality(rules)$count / quality(rules)$confidence))
quality(rules)$confidence <- estimatedConfidence
rules.nonredundant <- rules[!is.redundant(rules)]
inspect(head(rules.nonredundant))
BTW: You might want to look at Laplace Corrected Confidence ( http://michael.hahsler.net/research/association_rules/measures.html#laplace ) which can be calculated using the function interestMeasure()
. 顺便说一句:您可能想看一下拉普拉斯校正后的置信度( http://michael.hahsler.net/research/association_rules/measures.html#laplace ),该函数可以使用functioninterestMeasure interestMeasure()
进行计算。
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