R语言中关联规则的实现与可视化
2014-08-01 10:57阅读：
> require(arules)
#载入arules(Association
Rules)包
Warning message:
package ‘arules’ was built under R version 3.1.1
> require(arulesViz)
#载入arulesViz关联规则可视化工具包
Loading required package: arulesViz
Loading required package: grid
Attaching package: ‘arulesViz’
The following object is masked from
‘package:base’:
abbreviate
Warning message:
package ‘arulesViz’ was built under R version
3.1.1
> data(Groceries)
#载入Groceries数据集，包含9000多购买数据
> summary(Groceries)
#查看该数据集的汇总信息
transactions as itemMatrix in sparse format with
9835 rows (elements/itemsets/transactions)
and
169 columns (items) and a density of
0.02609146
most frequent items:
whole milk other
vegetables
rolls/buns
soda
yogurt
(Other)
2513
1903
1809
1715
1372
34055
element (itemset/transaction) length
distribution:
sizes
1 2
3 4 5
6 7
8 9 10
11 12 13 14
15 16 17
18 19 20 21
22 23 24
26 27
2159 1643 1299 1005 855 645 545
438 350 246 182 117
78 77 55 46
29 14 14
9 11 4
6 1
1 1
28 29 32
1 3
1
Min. 1st Qu. Median
Mean 3rd Qu. Max.
1.000 2.000 3.000
4.409 6.000
32.000
includes extended item information - examples:
labels
level2
level1
1 frankfurter sausage meet and sausage
2 sausage sausage meet and
sausage
3 liver loaf sausage meet and sausage
> inspect(head(Groceries))
#了解前五组数据的详细情况
items
1 {citrus fruit,
semi-finished bread,
margarine,
ready soups}
2 {tropical fruit,
yogurt,
coffee}
3 {whole milk}
4 {pip fruit,
yogurt,
cream cheese ,
meat spreads}
5 {other vegetables,
whole milk,
condensed milk,
long life bakery product}
6 {whole milk,
butter,
yogurt,
rice,
abrasive cleaner}
> rule0 <- apriori(Groceries)
parameter specification:
confidence minval smax arem aval
originalSupport support minlen maxlen target
ext
0.8
0.1 1 none FALSE
TRUE 0.1
1
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 ... [8 item(s)] done
[0.00s].
creating transaction tree ... done [0.00s].
checking subsets of size 1 2 done [0.00s].
writing ... [0 rule(s)] done [0.00s].
creating S4 object ... done [0.00s].
>
#以上使用apriori算法的默认参数进行运算
>
#用inspect查看具体生成的规则
> inspect(rule0)
NULL
>
#手动设置apriori算法的相关参数，包括support与confidence
> rule1 <-
apriori(Groceries,parameter=list(support=0.01,confidence=0.5))
parameter specification:
confidence minval smax arem aval
originalSupport support minlen maxlen target
ext
0.5
0.1 1 none FALSE
TRUE 0.01
1
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 ... [88 item(s)] done
[0.00s].
creating transaction tree ... done [0.03s].
checking subsets of size 1 2 3 4 done [0.00s].
writing ... [15 rule(s)] done [0.00s].
creating S4 object ... done [0.00s].
> inspect(rule1)
lhs
rhs
support confidence
lift
1
