Database Reference
In-Depth Information
rules <- apriori(Groceries, parameter=list(support=0.001,
confidence=0.6, target = "rules"))
parameter specification:
confidence minval smax arem aval originalSupport support
minlen
0.6 0.1 1 none FALSE TRUE 0.001 1
maxlen target ext
10 rules 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 …[169 item(s), 9835 transaction(s)] done
[0.00s].
sorting and recoding items … [157 item(s)] done [0.00s].
creating transaction tree … done [0.00s].
checking subsets of size 1 2 3 4 5 6 done [0.01s].
writing … [2918 rule(s)] done [0.00s].
creating S4 object … done [0.01s].
The summary of the rules shows the number of rules and ranges of the support,
confidence, and lift.
summary(rules)
set of 2918 rules
rule length distribution (lhs + rhs):sizes
2 3 4 5 6
3 490 1765 626 34
Min. 1st Qu. Median Mean 3rd Qu. Max.
2.000 4.000 4.000 4.068 4.000 6.000
summary of quality measures:
support confidence lift
Min. :0.001017 Min. :0.6000 Min. : 2.348
1st Qu.:0.001118 1st Qu.:0.6316 1st Qu.: 2.668
Median :0.001220 Median :0.6818 Median : 3.168
Mean :0.001480 Mean :0.7028 Mean : 3.450
3rd Qu.:0.001525 3rd Qu.:0.7500 3rd Qu.: 3.692
