我正在使用 4547 x 5415 的大型二进制数据矩阵进行关联规则挖掘。通常,每一行都是一个事务,每一列都是一个项目。每当我调用 arules 包时,它都会产生一些引用 trio 库的神秘错误消息。有没有人遇到过这种类型的错误?
i[1:10,1:10]
101402 101403 101404 101405 101406 101411 101412 101413 101414 101415
[1,] 0 0 0 1 0 0 1 0 0 0
[2,] 0 1 0 0 0 0 1 0 0 0
[3,] 0 0 0 0 0 0 1 0 0 0
[4,] 0 0 0 1 0 0 0 0 0 1
[5,] 0 0 0 1 0 0 0 0 0 1
[6,] 0 1 0 0 0 1 0 0 0 0
[7,] 0 0 0 0 0 0 1 0 0 0
[8,] 0 0 1 0 0 0 0 0 0 1
[9,] 0 0 0 0 0 1 0 0 0 0
[10,] 0 0 0 0 1 0 1 0 0 0
rules <- apriori(i, parameter=list(support=0.001, confidence=0.5))
parameter specification:
confidence minval smax arem aval originalSupport support minlen maxlen target
0.5 0.1 1 none FALSE TRUE 0.001 1 10 rules
ext
FALSE
algorithmic control:
filter tree heap memopt load sort verbose
0.1 TRUE TRUE FALSE TRUE 2 TRUE
apriori - find association rules with the apriori algorithm
version 4.21 (2004.05.09) (c) 1996-2004 Christian Borgelt
set item appearances ...[0 item(s)] done [0.00s].
set transactions ...[5415 item(s), 4547 transaction(s)] done [0.47s].
sorting and recoding items ... [4908 item(s)] done [0.18s].
creating transaction tree ... done [0.01s].
**checking subsets of size 1 2Error in apriori(i, parameter = list(support = 0.001, confidence = 0.5)) :
internal error in trio library**
可重现的例子:
y <- matrix(nrow=4547, ncol=5415)
y <- apply(y, c(1,2), function(x) sample(c(0,1),1))
rules <- apriori(y, parameter=list(support=0.001, confidence=0.5))