R version 2.9.2 (2009-08-24)
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ISBN 3-900051-07-0
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>
>
> # if necessary,
> #
> # install.packages("arules")
>
> library(arules)
Loading required package: Matrix
Loading required package: lattice
Attaching package: 'Matrix'
The following object(s) are masked from package:stats :
contr.helmert,
contr.poly,
contr.SAS,
contr.sum,
contr.treatment,
xtabs
The following object(s) are masked from package:base :
rcond
Attaching package: 'arules'
The following object(s) are masked from package:base :
%in%
>
> # a data set that is setup for predicting (income > 50k)
> # but we will ignore that for now
>
> data(Adult)
>
> adult.rules = apriori(Adult, parameter=list(confidence=0.8))
parameter specification:
confidence minval smax arem aval originalSupport support minlen maxlen target
0.8 0.1 1 none FALSE TRUE 0.1 1 5 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 ...[115 item(s), 48842 transaction(s)] done [0.09s].
sorting and recoding items ... [31 item(s)] done [0.02s].
creating transaction tree ... done [0.12s].
checking subsets of size 1 2 3 4 5 done [0.16s].
writing ... [4175 rule(s)] done [0.00s].
creating S4 object ... done [0.04s].
>
> # print out rules sorted by support
>
> inspect(SORT(adult.rules, by='support')[1:10])
lhs rhs support confidence lift
1 {} => {capital-loss=None} 0.9532779 0.9532779 1.0000000
2 {} => {capital-gain=None} 0.9173867 0.9173867 1.0000000
3 {} => {native-country=United-States} 0.8974243 0.8974243 1.0000000
4 {capital-gain=None} => {capital-loss=None} 0.8706646 0.9490705 0.9955863
5 {capital-loss=None} => {capital-gain=None} 0.8706646 0.9133376 0.9955863
6 {} => {race=White} 0.8550428 0.8550428 1.0000000
7 {native-country=United-States} => {capital-loss=None} 0.8548380 0.9525461 0.9992323
8 {capital-loss=None} => {native-country=United-States} 0.8548380 0.8967354 0.9992323
9 {native-country=United-States} => {capital-gain=None} 0.8219565 0.9159062 0.9983862
10 {capital-gain=None} => {native-country=United-States} 0.8219565 0.8959761 0.9983862
>
> # print out rules sorted by confidence
>
> inspect(SORT(adult.rules, by='confidence')[1:10])
lhs rhs support confidence lift
1 {relationship=Husband,
income=large} => {sex=Male} 0.1211662 1 1.495926
2 {relationship=Husband,
hours-per-week=Over-time} => {sex=Male} 0.1472298 1 1.495926
3 {age=Senior,
relationship=Husband} => {sex=Male} 0.1479874 1 1.495926
4 {marital-status=Married-civ-spouse,
relationship=Husband,
income=large} => {sex=Male} 0.1210843 1 1.495926
5 {relationship=Husband,
race=White,
income=large} => {sex=Male} 0.1111339 1 1.495926
6 {relationship=Husband,
native-country=United-States,
income=large} => {sex=Male} 0.1110724 1 1.495926
7 {relationship=Husband,
capital-loss=None,
income=large} => {sex=Male} 0.1086155 1 1.495926
8 {marital-status=Married-civ-spouse,
relationship=Husband,
hours-per-week=Over-time} => {sex=Male} 0.1471275 1 1.495926
9 {relationship=Husband,
race=White,
hours-per-week=Over-time} => {sex=Male} 0.1387126 1 1.495926
10 {relationship=Husband,
hours-per-week=Over-time,
native-country=United-States} => {sex=Male} 0.1366447 1 1.495926
>
> # find rules that force income to be on the RHS
>
> adult.rules = apriori(Adult, appearance=list(rhs=c("income=small", "income=large")), parameter=list(confidence=0.5))
parameter specification:
confidence minval smax arem aval originalSupport support minlen maxlen target
0.5 0.1 1 none FALSE TRUE 0.1 1 5 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 ...[2 item(s)] done [0.00s].
set transactions ...[115 item(s), 48842 transaction(s)] done [0.08s].
sorting and recoding items ... [31 item(s)] done [0.02s].
creating transaction tree ... done [0.12s].
checking subsets of size 1 2 3 4 5 done [0.18s].
writing ... [5401 rule(s)] done [0.00s].
creating S4 object ... done [0.04s].
> inspect(SORT(adult.rules, by='lift')[1:10])
lhs rhs support confidence lift
1 {age=Young,
marital-status=Never-married,
capital-gain=None} => {relationship=Own-child} 0.1014291 0.6181682 3.982663
2 {age=Young,
marital-status=Never-married} => {relationship=Own-child} 0.1038860 0.6165998 3.972559
3 {age=Young,
marital-status=Never-married,
capital-loss=None} => {relationship=Own-child} 0.1015315 0.6164843 3.971815
4 {marital-status=Never-married,
relationship=Own-child,
capital-gain=None} => {age=Young} 0.1014291 0.7541483 3.826125
5 {marital-status=Never-married,
relationship=Own-child,
capital-loss=None} => {age=Young} 0.1015315 0.7517053 3.813731
6 {marital-status=Never-married,
relationship=Own-child} => {age=Young} 0.1038860 0.7517037 3.813723
7 {relationship=Own-child,
capital-gain=None,
capital-loss=None} => {age=Young} 0.1020433 0.6942471 3.522221
8 {relationship=Own-child,
capital-gain=None} => {age=Young} 0.1045412 0.6939386 3.520655
9 {age=Young,
capital-gain=None} => {relationship=Own-child} 0.1045412 0.5462131 3.519079
10 {age=Young,
capital-gain=None,
capital-loss=None} => {relationship=Own-child} 0.1020433 0.5461319 3.518556
>
> # find rules that force income to be on the RHS and everything else on LHS
>
> adult.rules = apriori(Adult, appearance=list(rhs=c("income=small", "income=large"), default='lhs'), parameter=list(confidence=0.5))
parameter specification:
confidence minval smax arem aval originalSupport support minlen maxlen target
0.5 0.1 1 none FALSE TRUE 0.1 1 5 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 ...[2 item(s)] done [0.00s].
set transactions ...[115 item(s), 48842 transaction(s)] done [0.10s].
sorting and recoding items ... [31 item(s)] done [0.02s].
creating transaction tree ... done [0.12s].
checking subsets of size 1 2 3 4 5 done [0.16s].
writing ... [261 rule(s)] done [0.00s].
creating S4 object ... done [0.05s].
> inspect(SORT(adult.rules, by='lift')[1:10])
lhs rhs support confidence lift
1 {age=Young,
workclass=Private,
capital-loss=None} => {income=small} 0.1005282 0.6633342 1.310622
2 {age=Young,
workclass=Private} => {income=small} 0.1025961 0.6630938 1.310147
3 {age=Young,
marital-status=Never-married,
capital-gain=None,
capital-loss=None} => {income=small} 0.1060563 0.6616426 1.307279
4 {age=Young,
marital-status=Never-married,
capital-gain=None} => {income=small} 0.1084517 0.6609683 1.305947
5 {relationship=Own-child,
capital-loss=None} => {income=small} 0.1000983 0.6604972 1.305016
6 {relationship=Own-child} => {income=small} 0.1023914 0.6596755 1.303393
7 {age=Young,
marital-status=Never-married,
capital-loss=None} => {income=small} 0.1086360 0.6596221 1.303287
8 {age=Young,
marital-status=Never-married} => {income=small} 0.1110315 0.6590108 1.302080
9 {age=Young,
capital-gain=None,
capital-loss=None} => {income=small} 0.1229475 0.6580101 1.300102
10 {age=Young,
capital-gain=None} => {income=small} 0.1256910 0.6567180 1.297549
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> proc.time()
user system elapsed
8.740 0.112 10.011
R script