Association rules
Islam Islamov
2/7/2022
My data is about the transaction of a shop. But the size is most probably small since the products are only those needed for daily use.
PRODUCTS:
1.Bread 2.Cheese 3.Milk 4.Meat 5.Eggs 6.Wine 7.Bagel 8.Diaper 9.Pencil
So, we can see that there is not a lot of relation between the products already, however, as we will see later on there actually is some relation, but not huge.
Loading packages and preparing dataset.
library(arulesViz)## Loading required package: arules## Loading required package: Matrix##
## Attaching package: 'arules'## The following objects are masked from 'package:base':
##
## abbreviate, writelibrary(arules)
data <- read.transactions("C:\\Users\\Lelo\\Downloads\\retail_dataset.csv", sep = ",", header = T)Here we will inspect our dataset. Mainly to see the summary about it, as well as size and length of our dataset.
summary(data)## transactions as itemMatrix in sparse format with
## 315 rows (elements/itemsets/transactions) and
## 9 columns (items) and a density of 0.4504409
##
## most frequent items:
## Bread Cheese Milk Meat Eggs (Other)
## 159 158 158 150 138 514
##
## element (itemset/transaction) length distribution:
## sizes
## 1 2 3 4 5 6 7
## 30 40 58 54 62 30 41
##
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.000 3.000 4.000 4.054 5.000 7.000
##
## includes extended item information - examples:
## labels
## 1 Bagel
## 2 Bread
## 3 Cheeselength(data)## [1] 315Here you can witness simple statistics on frequency. We will use following function, that is mainly used to get the single item support from an object of class transactions without mining.
Absolute frequency shows the number of times the value is repeated in the data vector.
itemFrequency(data, type="absolute")## Bagel Bread Cheese Diaper Eggs Meat Milk Pencil Wine
## 134 159 158 128 138 150 158 114 138Relative frequency is the absolute frequency of that event divided by the total number of events.
itemFrequency(data, type="relative")## Bagel Bread Cheese Diaper Eggs Meat Milk Pencil
## 0.4253968 0.5047619 0.5015873 0.4063492 0.4380952 0.4761905 0.5015873 0.3619048
## Wine
## 0.4380952Look at the contents of a sparse matrix
inspect(data[1:10])## items
## [1] {Bread, Cheese, Diaper, Eggs, Meat, Pencil, Wine}
## [2] {Bread, Cheese, Diaper, Meat, Milk, Pencil, Wine}
## [3] {Cheese, Eggs, Meat, Milk, Wine}
## [4] {Cheese, Eggs, Meat, Milk, Wine}
## [5] {Meat, Pencil, Wine}
## [6] {Bagel, Bread, Diaper, Eggs, Milk, Pencil, Wine}
## [7] {Cheese, Eggs, Pencil, Wine}
## [8] {Bagel, Bread, Diaper, Milk, Pencil}
## [9] {Bread, Cheese, Diaper, Eggs, Milk, Wine}
## [10] {Bagel, Cheese, Diaper, Eggs, Meat, Pencil, Wine}Check the support level for the first five items in the data
itemFrequency(data[, 1:5])## Bagel Bread Cheese Diaper Eggs
## 0.4253968 0.5047619 0.5015873 0.4063492 0.4380952Note: The items in the sparse matrix are sorted in columns by alphabetical order
Support basically means how frequently an item set or a rule occurs in the data
We set the minimum support to 10% and run the code
itemFrequencyPlot(data, support = 0.1)
On the plot we can see that the most frequently occurring product is BREAD Now let’s limit the plot to a specific number of items (e.g. 15 ones).
itemFrequencyPlot(data, topN = 15)
Again, what wee see is that Bread occurs the most.
Visualize the sparse matrix for the first 5 items
image(data[1:5])
Random selection of 100 transactions
image(sample(data,100))
Find the association rules using the Apriori algorithm
Support at 0.6% (very low) and confidence at 25%, minimum length of a rule is 2 elements
Confidence represents the proportion of transactions
Where the presence of item or itemset X results in the presence of item or itemset Y
The choice of parameters is arbitrary, but there is a trade off between quality of measures and minimum length of a dataset, if one of them is high, then the second one need to be lower.
datarules <- apriori(data, parameter = list(support = 0.006, confidence = 0.25, minlen = 2))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.25 0.1 1 none FALSE TRUE 5 0.006 2
## maxlen target ext
## 10 rules TRUE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 1
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[9 item(s), 315 transaction(s)] done [0.00s].
## sorting and recoding items ... [9 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3 4 5 6 7 done [0.00s].
## writing ... [1954 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].datarules## set of 1954 rulessummary(datarules)## set of 1954 rules
##
## rule length distribution (lhs + rhs):sizes
## 2 3 4 5 6 7
## 72 252 496 609 422 103
##
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.000 4.000 5.000 4.699 6.000 7.000
##
## summary of quality measures:
## support confidence coverage lift
## Min. :0.006349 Min. :0.2500 Min. :0.006349 Min. :0.4953
## 1st Qu.:0.019048 1st Qu.:0.4118 1st Qu.:0.034921 1st Qu.:0.9345
## Median :0.031746 Median :0.5000 Median :0.063492 Median :1.1344
## Mean :0.048937 Mean :0.5128 Mean :0.096944 Mean :1.1380
## 3rd Qu.:0.063492 3rd Qu.:0.6000 3rd Qu.:0.114286 3rd Qu.:1.3156
## Max. :0.323809 Max. :1.0000 Max. :0.504762 Max. :2.3507
## count
## Min. : 2.00
## 1st Qu.: 6.00
## Median : 10.00
## Mean : 15.42
## 3rd Qu.: 20.00
## Max. :102.00
##
## mining info:
## data ntransactions support confidence
## data 315 0.006 0.25
## call
## apriori(data = data, parameter = list(support = 0.006, confidence = 0.25, minlen = 2))Look at specific rules
inspect(datarules[1:10])## lhs rhs support confidence coverage lift count
## [1] {Pencil} => {Diaper} 0.1714286 0.4736842 0.3619048 1.165707 54
## [2] {Diaper} => {Pencil} 0.1714286 0.4218750 0.4063492 1.165707 54
## [3] {Pencil} => {Bagel} 0.1587302 0.4385965 0.3619048 1.031029 50
## [4] {Bagel} => {Pencil} 0.1587302 0.3731343 0.4253968 1.031029 50
## [5] {Pencil} => {Eggs} 0.1650794 0.4561404 0.3619048 1.041190 52
## [6] {Eggs} => {Pencil} 0.1650794 0.3768116 0.4380952 1.041190 52
## [7] {Pencil} => {Wine} 0.2000000 0.5526316 0.3619048 1.261442 63
## [8] {Wine} => {Pencil} 0.2000000 0.4565217 0.4380952 1.261442 63
## [9] {Pencil} => {Meat} 0.1777778 0.4912281 0.3619048 1.031579 56
## [10] {Meat} => {Pencil} 0.1777778 0.3733333 0.4761905 1.031579 56Reorder the rules so that we are able to inspect the most meaningful ones. Following commands define the most important rules sorted by three major measures: support, lift and confidence.
Measure 1: Support. This says how popular an itemset is, as measured by the proportion of transactions in which an itemset appears.
inspect(sort(datarules, by = "support")[1:5])## lhs rhs support confidence coverage lift count
## [1] {Meat} => {Cheese} 0.3238095 0.6800000 0.4761905 1.355696 102
## [2] {Cheese} => {Meat} 0.3238095 0.6455696 0.5015873 1.355696 102
## [3] {Milk} => {Cheese} 0.3047619 0.6075949 0.5015873 1.211344 96
## [4] {Cheese} => {Milk} 0.3047619 0.6075949 0.5015873 1.211344 96
## [5] {Eggs} => {Cheese} 0.2984127 0.6811594 0.4380952 1.358008 94Measure 2: Confidence. This says how likely item Y is purchased when item X is purchased, expressed as {X -> Y}.
inspect(sort(datarules, by = "confidence")[1:5])## lhs rhs support confidence
## [1] {Bagel, Cheese, Diaper, Eggs, Pencil} => {Wine} 0.019047619 1
## [2] {Diaper, Eggs, Meat, Milk, Pencil} => {Bagel} 0.006349206 1
## [3] {Bagel, Diaper, Eggs, Milk, Pencil} => {Bread} 0.009523810 1
## [4] {Cheese, Diaper, Eggs, Meat, Pencil} => {Wine} 0.022222222 1
## [5] {Diaper, Eggs, Meat, Milk, Pencil} => {Bread} 0.006349206 1
## coverage lift count
## [1] 0.019047619 2.282609 6
## [2] 0.006349206 2.350746 2
## [3] 0.009523810 1.981132 3
## [4] 0.022222222 2.282609 7
## [5] 0.006349206 1.981132 2Measure 3: Lift. This says how likely item Y is purchased when item X is purchased, while controlling for how popular item Y is.
inspect(sort(datarules, by = "lift")[1:5])## lhs rhs support confidence
## [1] {Diaper, Eggs, Meat, Milk, Pencil} => {Bagel} 0.006349206 1
## [2] {Bread, Diaper, Eggs, Meat, Milk, Pencil} => {Bagel} 0.006349206 1
## [3] {Bagel, Cheese, Diaper, Eggs, Pencil} => {Wine} 0.019047619 1
## [4] {Cheese, Diaper, Eggs, Meat, Pencil} => {Wine} 0.022222222 1
## [5] {Cheese, Diaper, Meat, Milk, Pencil} => {Wine} 0.009523810 1
## coverage lift count
## [1] 0.006349206 2.350746 2
## [2] 0.006349206 2.350746 2
## [3] 0.019047619 2.282609 6
## [4] 0.022222222 2.282609 7
## [5] 0.009523810 2.282609 3Below we will look at what products, which drive people to buy wine.
rules.wine<-apriori(data=data, parameter=list(supp=0.01,conf = 0.005),
appearance=list(default="lhs", rhs="Wine"), control=list(verbose=F))
rules.wine.byconf<-sort(rules.wine, by="confidence", decreasing=TRUE)
inspect(head(rules.wine.byconf))## lhs rhs support confidence
## [1] {Bagel, Cheese, Diaper, Eggs, Pencil} => {Wine} 0.01904762 1.0000000
## [2] {Cheese, Diaper, Eggs, Meat, Pencil} => {Wine} 0.02222222 1.0000000
## [3] {Bagel, Cheese, Diaper, Eggs, Milk} => {Wine} 0.01269841 1.0000000
## [4] {Bagel, Cheese, Diaper, Eggs, Meat, Pencil} => {Wine} 0.01269841 1.0000000
## [5] {Cheese, Diaper, Eggs, Pencil} => {Wine} 0.04126984 0.8666667
## [6] {Cheese, Diaper, Meat, Pencil} => {Wine} 0.03809524 0.8571429
## coverage lift count
## [1] 0.01904762 2.282609 6
## [2] 0.02222222 2.282609 7
## [3] 0.01269841 2.282609 4
## [4] 0.01269841 2.282609 4
## [5] 0.04761905 1.978261 13
## [6] 0.04444444 1.956522 12We can see many different variables but let’s look closer for relation of each product.
What are other products that customers complement their wine purchase with?
rules.wineopp<-apriori(data=data, parameter=list(supp=0.01,conf = 0.005),
appearance=list(default="rhs", lhs="Wine"), control=list(verbose=F))
rules.wineopp.byconf<-sort(rules.wineopp, by="confidence", decreasing=TRUE)
inspect(head(rules.wineopp.byconf))## lhs rhs support confidence coverage lift count
## [1] {Wine} => {Cheese} 0.2698413 0.6159420 0.4380952 1.227986 85
## [2] {Wine} => {Meat} 0.2507937 0.5724638 0.4380952 1.202174 79
## [3] {Wine} => {Bread} 0.2444444 0.5579710 0.4380952 1.105414 77
## [4] {Wine} => {Eggs} 0.2412698 0.5507246 0.4380952 1.257089 76
## [5] {Wine} => {Diaper} 0.2349206 0.5362319 0.4380952 1.319633 74
## [6] {} => {Bread} 0.5047619 0.5047619 1.0000000 1.000000 159We can see that cheese is the most popular product bought with wine, meaning that we can make bundles of these products Or to simply shelf them side by side.
The confidence of Wine x Cheese is also higher, as well as the indicator of count too.
Also the confidence level is also the highest for the case of Wine x Cheese.
Now we can check significance of the rules with Fisher’s exact :
is.significant(rules.wine, data)## [1] FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE
## [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE
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## [181] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [193] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSERedundancy - Data redundancy occurs when the same piece of data is stored in two or more separate places and is a common occurrence in many businesses.
is.redundant(rules.wine)## [1] FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE TRUE FALSE
## [13] FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
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## [193] TRUE TRUE TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUEis.redundant(rules.wineopp)## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE
## [13] FALSE TRUE FALSE FALSElibrary(arulesCBA)##
## Attaching package: 'arulesCBA'## The following object is masked from 'package:arules':
##
## rulesNow we can plot now all three major indicators at the same times(support,confidence and lift:
plot(datarules, measure=c("support","lift"), shading="confidence")## To reduce overplotting, jitter is added! Use jitter = 0 to prevent jitter.
Other plots
plot(datarules)## To reduce overplotting, jitter is added! Use jitter = 0 to prevent jitter.
plot(rules.wine)## To reduce overplotting, jitter is added! Use jitter = 0 to prevent jitter.
plot(datarules, method="matrix", measure="lift")## Itemsets in Antecedent (LHS)
## [1] "{Bread,Diaper,Eggs,Meat,Milk,Pencil}"
## [2] "{Bagel,Cheese,Diaper,Eggs,Meat,Pencil}"
## [3] "{Bagel,Bread,Cheese,Diaper,Eggs,Pencil}"
## [4] "{Bagel,Bread,Diaper,Meat,Milk,Pencil}"
## [5] "{Bread,Cheese,Diaper,Eggs,Meat,Pencil}"
## [6] "{Bread,Cheese,Diaper,Meat,Milk,Pencil}"
## [7] "{Bagel,Cheese,Diaper,Eggs,Meat,Milk}"
## [8] "{Bagel,Bread,Cheese,Diaper,Eggs,Milk}"
## [9] "{Diaper,Eggs,Meat,Milk,Pencil}"
## [10] "{Cheese,Diaper,Meat,Milk,Pencil}"
## [11] "{Bread,Cheese,Diaper,Milk,Pencil,Wine}"
## [12] "{Bagel,Diaper,Eggs,Meat,Pencil,Wine}"
## [13] "{Bagel,Bread,Diaper,Eggs,Meat,Pencil}"
## [14] "{Bagel,Bread,Diaper,Meat,Pencil,Wine}"
## [15] "{Bread,Diaper,Eggs,Meat,Pencil,Wine}"
## [16] "{Bagel,Bread,Eggs,Meat,Pencil,Wine}"
## [17] "{Bagel,Diaper,Eggs,Meat,Milk,Pencil}"
## [18] "{Cheese,Diaper,Meat,Milk,Pencil,Wine}"
## [19] "{Bagel,Cheese,Eggs,Meat,Pencil,Wine}"
## [20] "{Bagel,Diaper,Eggs,Milk,Pencil}"
## [21] "{Cheese,Eggs,Meat,Milk,Pencil,Wine}"
## [22] "{Bagel,Cheese,Eggs,Meat,Milk,Wine}"
## [23] "{Bread,Cheese,Eggs,Meat,Milk,Pencil}"
## [24] "{Diaper,Meat,Milk,Pencil,Wine}"
## [25] "{Bagel,Bread,Eggs,Meat,Milk}"
## [26] "{Bagel,Cheese,Diaper,Milk,Pencil}"
## [27] "{Bagel,Bread,Cheese,Eggs,Milk,Pencil}"
## [28] "{Bagel,Bread,Cheese,Meat,Milk,Pencil}"
## [29] "{Cheese,Diaper,Eggs,Meat,Pencil}"
## [30] "{Bagel,Bread,Cheese,Eggs,Milk}"
## [31] "{Cheese,Diaper,Meat,Pencil}"
## [32] "{Bagel,Cheese,Diaper,Eggs,Pencil}"
## [33] "{Bagel,Cheese,Meat,Milk,Pencil}"
## [34] "{Bagel,Cheese,Diaper,Eggs,Milk}"
## [35] "{Eggs,Meat,Milk,Pencil}"
## [36] "{Bagel,Diaper,Meat,Milk,Pencil}"
## [37] "{Bagel,Cheese,Eggs,Milk,Pencil}"
## [38] "{Diaper,Eggs,Meat,Milk,Wine}"
## [39] "{Bagel,Bread,Diaper,Eggs,Milk,Pencil}"
## [40] "{Bagel,Diaper,Meat,Milk,Wine}"
## [41] "{Diaper,Eggs,Meat,Milk}"
## [42] "{Bagel,Bread,Eggs,Milk}"
## [43] "{Bread,Meat,Milk}"
## [44] "{Bread,Cheese,Eggs,Milk,Pencil}"
## [45] "{Bread,Cheese,Eggs,Meat,Wine}"
## [46] "{Cheese,Diaper,Meat,Milk}"
## [47] "{Cheese,Eggs,Meat,Milk,Pencil}"
## [48] "{Bread,Eggs,Milk}"
## [49] "{Bread,Eggs,Meat}"
## [50] "{Diaper,Meat,Milk}"
## [51] "{Bagel,Eggs,Milk}"
## [52] "{Diaper,Eggs,Meat,Pencil}"
## [53] "{Bagel,Diaper,Milk,Pencil,Wine}"
## [54] "{Bagel,Bread,Diaper,Eggs,Pencil,Wine}"
## [55] "{Bagel,Bread,Diaper,Eggs,Meat,Wine}"
## [56] "{Bread,Cheese,Eggs,Milk}"
## [57] "{Bagel,Cheese,Eggs,Milk,Pencil,Wine}"
## [58] "{Bagel,Cheese,Meat,Milk,Pencil,Wine}"
## [59] "{Bread,Cheese,Eggs,Meat,Milk}"
## [60] "{Bagel,Bread,Eggs,Meat,Milk,Wine}"
## [61] "{Bagel,Bread,Cheese,Eggs,Milk,Wine}"
## [62] "{Eggs,Meat,Milk,Pencil,Wine}"
## [63] "{Bagel,Diaper,Eggs,Milk}"
## [64] "{Bread,Meat}"
## [65] "{Bread,Milk,Wine}"
## [66] "{Bagel,Cheese,Diaper,Meat,Pencil}"
## [67] "{Bagel,Diaper,Eggs}"
## [68] "{Bagel,Meat,Milk,Pencil,Wine}"
## [69] "{Bagel,Bread,Meat,Milk}"
## [70] "{Cheese,Meat,Milk,Pencil}"
## [71] "{Bread,Meat,Milk,Pencil}"
## [72] "{Bread,Meat,Milk,Wine}"
## [73] "{Bread,Cheese,Eggs,Wine}"
## [74] "{Bagel,Bread,Diaper,Pencil,Wine}"
## [75] "{Bread,Eggs,Meat,Milk}"
## [76] "{Bread,Eggs,Meat,Milk,Pencil}"
## [77] "{Bagel,Bread,Diaper,Eggs,Meat,Milk}"
## [78] "{Bread,Meat,Wine}"
## [79] "{Eggs,Meat,Pencil}"
## [80] "{Bagel,Bread,Milk,Pencil,Wine}"
## [81] "{Bagel,Wine}"
## [82] "{Diaper,Meat,Milk,Wine}"
## [83] "{Bagel,Diaper,Eggs,Milk,Wine}"
## [84] "{Bagel,Bread,Pencil,Wine}"
## [85] "{Bread,Cheese,Wine}"
## [86] "{Bread,Cheese,Meat}"
## [87] "{Bagel,Meat,Milk,Wine}"
## [88] "{Bread,Cheese}"
## [89] "{Cheese,Diaper}"
## [90] "{Bagel,Bread,Diaper,Eggs}"
## [91] "{Bagel,Eggs,Wine}"
## [92] "{Bread,Eggs,Meat,Pencil,Wine}"
## [93] "{Bagel,Bread,Cheese,Milk}"
## [94] "{Bagel,Cheese,Wine}"
## [95] "{Bread,Cheese,Eggs}"
## [96] "{Bread,Eggs,Meat,Pencil}"
## [97] "{Eggs,Milk,Pencil,Wine}"
## [98] "{Bagel,Milk,Wine}"
## [99] "{Bagel,Bread,Cheese,Milk,Pencil}"
## [100] "{Bread,Cheese,Milk}"
## [101] "{Bagel,Diaper,Eggs,Wine}"
## [102] "{Bagel,Meat,Milk}"
## [103] "{Bagel,Cheese,Diaper,Pencil}"
## [104] "{Bread,Cheese,Milk,Wine}"
## [105] "{Bread,Diaper,Eggs}"
## [106] "{Bagel,Bread,Cheese}"
## [107] "{Bread,Eggs,Wine}"
## [108] "{Bread,Cheese,Meat,Milk}"
## [109] "{Bread,Eggs,Pencil}"
## [110] "{Bread,Cheese,Eggs,Meat}"
## [111] "{Bread,Eggs}"
## [112] "{Cheese,Diaper,Eggs}"
## [113] "{Bread,Cheese,Meat,Wine}"
## [114] "{Bread,Diaper,Meat,Milk}"
## [115] "{Bread,Eggs,Milk,Wine}"
## [116] "{Cheese,Eggs,Meat,Pencil}"
## [117] "{Bread,Milk,Pencil}"
## [118] "{Bagel,Eggs,Meat,Pencil}"
## [119] "{Bread,Cheese,Milk,Pencil,Wine}"
## [120] "{Cheese,Diaper,Meat}"
## [121] "{Milk,Wine}"
## [122] "{Milk,Pencil,Wine}"
## [123] "{Eggs,Pencil}"
## [124] "{Cheese,Diaper,Eggs,Meat,Milk}"
## [125] "{Bread,Cheese,Pencil,Wine}"
## [126] "{Bagel,Diaper,Pencil,Wine}"
## [127] "{Meat,Milk,Pencil,Wine}"
## [128] "{Diaper,Milk}"
## [129] "{Bread,Diaper,Eggs,Meat}"
## [130] "{Bread,Pencil,Wine}"
## [131] "{Cheese,Wine}"
## [132] "{Bagel,Milk,Pencil,Wine}"
## [133] "{Bagel,Bread,Cheese,Wine}"
## [134] "{Bagel,Eggs,Meat,Milk}"
## [135] "{Bagel,Eggs,Milk,Pencil}"
## [136] "{Cheese,Meat,Pencil}"
## [137] "{Cheese,Meat,Pencil,Wine}"
## [138] "{Bagel,Eggs,Pencil}"
## [139] "{Diaper,Eggs,Meat}"
## [140] "{Bagel,Cheese,Diaper,Meat,Milk}"
## [141] "{Bagel,Bread,Wine}"
## [142] "{Bagel,Bread,Milk,Wine}"
## [143] "{Bread,Meat,Pencil}"
## [144] "{Bagel,Cheese,Eggs}"
## [145] "{Bread,Cheese,Eggs,Meat,Pencil}"
## [146] "{Bagel,Eggs,Milk,Wine}"
## [147] "{Diaper,Milk,Wine}"
## [148] "{Bread,Diaper,Meat,Milk,Pencil,Wine}"
## [149] "{Bagel,Cheese,Eggs,Wine}"
## [150] "{Meat,Milk,Wine}"
## [151] "{Bagel,Diaper,Meat,Pencil,Wine}"
## [152] "{Bread,Diaper,Meat}"
## [153] "{Diaper,Eggs}"
## [154] "{Bagel,Eggs,Meat}"
## [155] "{Cheese,Diaper,Pencil}"
## [156] "{Cheese,Diaper,Eggs,Wine}"
## [157] "{Eggs,Meat,Milk}"
## [158] "{Bagel,Cheese,Eggs,Milk}"
## [159] "{Cheese,Pencil,Wine}"
## [160] "{Bagel,Cheese}"
## [161] "{Bread,Cheese,Pencil}"
## [162] "{Diaper,Eggs,Milk}"
## [163] "{Bread,Cheese,Milk,Pencil}"
## [164] "{Bread,Wine}"
## [165] "{Bagel,Bread,Eggs,Wine}"
## [166] "{Cheese,Eggs,Pencil}"
## [167] "{Bread,Eggs,Meat,Wine}"
## [168] "{Bagel,Bread,Cheese,Meat,Milk}"
## [169] "{Bagel,Eggs}"
## [170] "{Bagel,Meat,Milk,Pencil}"
## [171] "{Cheese,Diaper,Milk}"
## [172] "{Bagel,Bread,Eggs}"
## [173] "{Bagel,Bread,Cheese,Meat,Wine}"
## [174] "{Bagel,Pencil,Wine}"
## [175] "{Bread,Pencil}"
## [176] "{Eggs,Milk,Pencil}"
## [177] "{Pencil,Wine}"
## [178] "{Bagel,Diaper,Eggs,Pencil}"
## [179] "{Meat,Wine}"
## [180] "{Bagel,Meat}"
## [181] "{Bagel,Cheese,Meat,Pencil}"
## [182] "{Bread,Cheese,Eggs,Meat,Milk,Wine}"
## [183] "{Eggs,Wine}"
## [184] "{Bread,Eggs,Milk,Pencil}"
## [185] "{Bread,Cheese,Eggs,Milk,Pencil,Wine}"
## [186] "{Meat,Milk,Pencil}"
## [187] "{Cheese,Diaper,Meat,Wine}"
## [188] "{Cheese,Pencil}"
## [189] "{Wine}"
## [190] "{Bagel,Cheese,Diaper}"
## [191] "{Bagel,Meat,Wine}"
## [192] "{Diaper,Meat,Pencil}"
## [193] "{Cheese,Diaper,Eggs,Meat,Wine}"
## [194] "{Bread,Diaper,Eggs,Milk}"
## [195] "{Cheese,Diaper,Wine}"
## [196] "{Bread,Cheese,Diaper,Eggs}"
## [197] "{Bagel,Cheese,Eggs,Milk,Wine}"
## [198] "{Bagel,Cheese,Pencil,Wine}"
## [199] "{Bagel,Diaper,Meat,Milk}"
## [200] "{Bread,Diaper}"
## [201] "{Meat,Pencil}"
## [202] "{Cheese,Meat,Wine}"
## [203] "{Meat,Pencil,Wine}"
## [204] "{Bread,Diaper,Milk}"
## [205] "{Bagel,Cheese,Meat,Wine}"
## [206] "{Bread,Cheese,Diaper}"
## [207] "{Bagel,Cheese,Diaper,Meat,Wine}"
## [208] "{Bagel,Bread,Milk,Pencil}"
## [209] "{Bagel,Bread,Diaper,Eggs,Milk}"
## [210] "{Bagel,Bread,Cheese,Eggs}"
## [211] "{Bagel,Cheese,Pencil}"
## [212] "{Cheese,Milk,Pencil,Wine}"
## [213] "{Bagel,Bread,Pencil}"
## [214] "{Diaper,Eggs,Wine}"
## [215] "{Bagel,Bread,Cheese,Diaper,Meat,Pencil}"
## [216] "{Bagel,Bread,Cheese,Diaper,Meat,Milk}"
## [217] "{Bread,Cheese,Diaper,Eggs,Meat,Milk}"
## [218] "{Diaper,Eggs,Milk,Wine}"
## [219] "{Cheese,Eggs,Wine}"
## [220] "{Bagel,Cheese,Diaper,Pencil,Wine}"
## [221] "{Diaper,Meat}"
## [222] "{Eggs,Milk,Wine}"
## [223] "{Bread,Cheese,Meat,Milk,Wine}"
## [224] "{Cheese}"
## [225] "{Bread,Cheese,Meat,Pencil,Wine}"
## [226] "{Bagel,Cheese,Milk}"
## [227] "{Bagel,Milk,Pencil}"
## [228] "{Eggs,Pencil,Wine}"
## [229] "{Bagel,Diaper,Wine}"
## [230] "{Bagel,Bread,Eggs,Milk,Wine}"
## [231] "{Cheese,Diaper,Meat,Milk,Wine}"
## [232] "{Bagel,Cheese,Meat}"
## [233] "{Cheese,Milk,Wine}"
## [234] "{Bagel,Diaper,Meat}"
## [235] "{Bagel,Cheese,Milk,Wine}"
## [236] "{Bagel,Diaper}"
## [237] "{Bagel,Bread,Meat}"
## [238] "{Bagel,Cheese,Diaper,Milk}"
## [239] "{Cheese,Diaper,Eggs,Meat}"
## [240] "{Bagel,Bread,Meat,Milk,Pencil}"
## [241] "{Eggs,Meat,Pencil,Wine}"
## [242] "{Bagel,Cheese,Eggs,Meat,Wine}"
## [243] "{Bread,Eggs,Pencil,Wine}"
## [244] "{Cheese,Diaper,Pencil,Wine}"
## [245] "{Bagel,Cheese,Diaper,Wine}"
## [246] "{Bagel,Cheese,Diaper,Eggs,Wine}"
## [247] "{Milk,Pencil}"
## [248] "{Bread,Meat,Pencil,Wine}"
## [249] "{Cheese,Eggs,Milk,Pencil}"
## [250] "{Bread,Cheese,Eggs,Pencil}"
## [251] "{Bagel,Bread,Eggs,Meat}"
## [252] "{Bagel,Bread,Cheese,Eggs,Pencil,Wine}"
## [253] "{Bagel,Bread,Cheese,Meat,Pencil,Wine}"
## [254] "{Bagel,Cheese,Meat,Pencil,Wine}"
## [255] "{Bread,Eggs,Milk,Pencil,Wine}"
## [256] "{Diaper,Pencil}"
## [257] "{Bagel,Bread,Cheese,Eggs,Wine}"
## [258] "{Bread,Cheese,Meat,Milk,Pencil}"
## [259] "{Bagel,Cheese,Diaper,Eggs}"
## [260] "{Bagel,Pencil}"
## [261] "{Bagel,Diaper,Eggs,Meat,Milk}"
## [262] "{Bagel,Diaper,Milk,Wine}"
## [263] "{Bread,Cheese,Diaper,Eggs,Milk}"
## [264] "{Bagel,Bread,Cheese,Pencil,Wine}"
## [265] "{Bagel,Eggs,Pencil,Wine}"
## [266] "{Bread,Diaper,Eggs,Meat,Wine}"
## [267] "{Bagel,Diaper,Meat,Wine}"
## [268] "{Bread,Cheese,Diaper,Eggs,Pencil,Wine}"
## [269] "{Bagel,Diaper,Meat,Pencil}"
## [270] "{Bread,Cheese,Diaper,Meat}"
## [271] "{Cheese,Diaper,Eggs,Meat,Pencil,Wine}"
## [272] "{Bagel,Diaper,Eggs,Pencil,Wine}"
## [273] "{Diaper,Wine}"
## [274] "{Bagel,Bread,Cheese,Diaper,Pencil,Wine}"
## [275] "{Bagel,Bread,Cheese,Milk,Pencil,Wine}"
## [276] "{Bagel,Bread,Cheese,Diaper,Milk,Wine}"
## [277] "{Bagel,Diaper,Milk}"
## [278] "{Bagel,Eggs,Milk,Pencil,Wine}"
## [279] "{Bagel,Cheese,Diaper,Meat,Pencil,Wine}"
## [280] "{Bread,Cheese,Diaper,Pencil,Wine}"
## [281] "{Cheese,Meat,Milk,Pencil,Wine}"
## [282] "{Bread,Milk,Pencil,Wine}"
## [283] "{Meat,Milk}"
## [284] "{Bagel,Eggs,Meat,Wine}"
## [285] "{Bagel,Eggs,Meat,Milk,Wine}"
## [286] "{Bagel,Cheese,Eggs,Pencil}"
## [287] "{Meat}"
## [288] "{Cheese,Milk,Pencil}"
## [289] "{Eggs,Meat,Wine}"
## [290] "{Diaper,Eggs,Meat,Wine}"
## [291] "{Bread,Diaper,Eggs,Meat,Milk,Wine}"
## [292] "{Bagel,Diaper,Eggs,Meat}"
## [293] "{Diaper,Eggs,Meat,Pencil,Wine}"
## [294] "{Bread,Cheese,Eggs,Meat,Pencil,Wine}"
## [295] "{Pencil}"
## [296] "{Cheese,Diaper,Eggs,Meat,Milk,Wine}"
## [297] "{Eggs,Milk}"
## [298] "{Cheese,Diaper,Meat,Pencil,Wine}"
## [299] "{Bagel,Diaper,Eggs,Meat,Wine}"
## [300] "{Diaper,Meat,Wine}"
## [301] "{Bagel,Bread,Diaper,Eggs,Wine}"
## [302] "{Eggs}"
## [303] "{Diaper,Eggs,Pencil}"
## [304] "{Bread,Diaper,Eggs,Meat,Pencil}"
## [305] "{Bagel,Cheese,Diaper,Eggs,Meat,Wine}"
## [306] "{Cheese,Eggs,Milk}"
## [307] "{Diaper,Meat,Milk,Pencil}"
## [308] "{Bagel,Meat,Pencil}"
## [309] "{Cheese,Diaper,Eggs,Pencil}"
## [310] "{Bread,Diaper,Eggs,Milk,Wine}"
## [311] "{Bread,Diaper,Milk,Wine}"
## [312] "{Bagel,Bread,Meat,Milk,Pencil,Wine}"
## [313] "{Bagel,Bread,Diaper,Meat,Milk,Wine}"
## [314] "{Bread,Cheese,Meat,Pencil}"
## [315] "{Bread,Diaper,Pencil}"
## [316] "{Cheese,Meat}"
## [317] "{Cheese,Diaper,Eggs,Milk,Pencil}"
## [318] "{Bagel,Cheese,Diaper,Meat,Milk,Wine}"
## [319] "{Bagel,Bread,Cheese,Milk,Wine}"
## [320] "{Cheese,Eggs}"
## [321] "{Bread,Cheese,Diaper,Milk}"
## [322] "{Bagel,Bread,Cheese,Meat}"
## [323] "{Bagel,Bread,Meat,Pencil,Wine}"
## [324] "{Bread,Diaper,Eggs,Pencil}"
## [325] "{Bread,Diaper,Meat,Wine}"
## [326] "{Bagel,Bread,Meat,Pencil}"
## [327] "{Bread,Diaper,Meat,Milk,Wine}"
## [328] "{Bagel,Bread,Cheese,Diaper,Milk}"
## [329] "{Bagel,Bread,Diaper,Eggs,Pencil}"
## [330] "{Cheese,Diaper,Milk,Wine}"
## [331] "{Bagel,Bread,Meat,Milk,Wine}"
## [332] "{Bread,Eggs,Meat,Milk,Wine}"
## [333] "{Bread,Eggs,Meat,Milk,Pencil,Wine}"
## [334] "{Bread}"
## [335] "{Eggs,Meat}"
## [336] "{Diaper,Pencil,Wine}"
## [337] "{Cheese,Meat,Milk}"
## [338] "{Bagel,Bread,Diaper}"
## [339] "{Bagel,Bread,Meat,Wine}"
## [340] "{Bread,Cheese,Diaper,Eggs,Wine}"
## [341] "{Cheese,Milk}"
## [342] "{Bagel,Diaper,Eggs,Meat,Pencil}"
## [343] "{Cheese,Eggs,Milk,Wine}"
## [344] "{Bread,Diaper,Eggs,Wine}"
## [345] "{Bagel,Bread,Eggs,Milk,Pencil}"
## [346] "{Bagel,Cheese,Eggs,Meat,Pencil}"
## [347] "{Diaper}"
## [348] "{Cheese,Eggs,Milk,Pencil,Wine}"
## [349] "{Bagel,Meat,Pencil,Wine}"
## [350] "{Bagel,Cheese,Diaper,Eggs,Pencil,Wine}"
## [351] "{Bagel,Bread,Diaper,Milk,Wine}"
## [352] "{Bread,Meat,Milk,Pencil,Wine}"
## [353] "{Bread,Cheese,Eggs,Milk,Wine}"
## [354] "{Bread,Cheese,Diaper,Pencil}"
## [355] "{Bagel,Bread,Eggs,Pencil}"
## [356] "{Milk}"
## [357] "{Bread,Cheese,Diaper,Meat,Wine}"
## [358] "{Bread,Cheese,Diaper,Wine}"
## [359] "{Bagel,Bread,Cheese,Pencil}"
## [360] "{Bagel,Cheese,Meat,Milk,Wine}"
## [361] "{Bread,Cheese,Diaper,Eggs,Meat,Wine}"
## [362] "{Bread,Diaper,Wine}"
## [363] "{Bread,Milk}"
## [364] "{Bagel,Cheese,Diaper,Meat}"
## [365] "{Bagel,Cheese,Diaper,Eggs,Milk,Wine}"
## [366] "{Diaper,Eggs,Pencil,Wine}"
## [367] "{Bread,Diaper,Meat,Pencil}"
## [368] "{Bread,Diaper,Pencil,Wine}"
## [369] "{Cheese,Eggs,Meat,Pencil,Wine}"
## [370] "{Bread,Cheese,Diaper,Meat,Pencil}"
## [371] "{Cheese,Eggs,Pencil,Wine}"
## [372] "{Diaper,Milk,Pencil}"
## [373] "{Bagel,Diaper,Pencil}"
## [374] "{Cheese,Diaper,Eggs,Milk}"
## [375] "{Bread,Cheese,Eggs,Pencil,Wine}"
## [376] "{Bagel}"
## [377] "{Bread,Diaper,Milk,Pencil,Wine}"
## [378] "{Bread,Diaper,Eggs,Meat,Milk}"
## [379] "{Cheese,Meat,Milk,Wine}"
## [380] "{Bagel,Eggs,Meat,Milk,Pencil}"
## [381] "{Diaper,Meat,Pencil,Wine}"
## [382] "{Bagel,Bread,Cheese,Diaper}"
## [383] "{Eggs,Meat,Milk,Wine}"
## [384] "{Diaper,Eggs,Milk,Pencil,Wine}"
## [385] "{Bagel,Diaper,Eggs,Meat,Milk,Wine}"
## [386] "{Cheese,Diaper,Eggs,Pencil,Wine}"
## [387] "{Bagel,Bread,Diaper,Meat,Milk}"
## [388] "{Bagel,Eggs,Meat,Pencil,Wine}"
## [389] "{Diaper,Milk,Pencil,Wine}"
## [390] "{Bagel,Eggs,Meat,Milk,Pencil,Wine}"
## [391] "{Cheese,Diaper,Eggs,Milk,Wine}"
## [392] "{Bagel,Bread,Eggs,Pencil,Wine}"
## [393] "{Bagel,Cheese,Eggs,Pencil,Wine}"
## [394] "{Bagel,Cheese,Eggs,Meat}"
## [395] "{Bagel,Bread,Eggs,Meat,Pencil}"
## [396] "{Bagel,Cheese,Meat,Milk}"
## [397] "{Bread,Cheese,Diaper,Meat,Milk}"
## [398] "{Bagel,Bread,Cheese,Diaper,Eggs}"
## [399] "{Bagel,Bread,Cheese,Eggs,Meat}"
## [400] "{Bread,Cheese,Diaper,Milk,Wine}"
## [401] "{Bagel,Cheese,Eggs,Meat,Milk}"
## [402] "{Bread,Diaper,Meat,Milk,Pencil}"
## [403] "{Cheese,Diaper,Milk,Pencil}"
## [404] "{Bagel,Bread,Cheese,Diaper,Eggs,Wine}"
## [405] "{Bagel,Bread,Cheese,Diaper,Meat,Wine}"
## [406] "{Bagel,Bread,Eggs,Meat,Milk,Pencil}"
## [407] "{Cheese,Eggs,Meat,Wine}"
## [408] "{Bread,Cheese,Diaper,Eggs,Pencil}"
## [409] "{Bagel,Bread,Diaper,Eggs,Meat}"
## [410] "{Bread,Cheese,Meat,Milk,Pencil,Wine}"
## [411] "{Bagel,Bread,Diaper,Meat}"
## [412] "{Bagel,Bread,Diaper,Milk}"
## [413] "{Bagel,Bread,Cheese,Diaper,Wine}"
## [414] "{Bagel,Bread,Diaper,Wine}"
## [415] "{Bread,Cheese,Diaper,Eggs,Meat}"
## [416] "{Bagel,Bread,Cheese,Meat,Pencil}"
## [417] "{Bagel,Bread,Diaper,Milk,Pencil}"
## [418] "{Bagel,Bread,Cheese,Diaper,Pencil}"
## [419] "{Bagel,Cheese,Milk,Pencil}"
## [420] "{Bagel,Cheese,Diaper,Eggs,Meat}"
## [421] "{Bread,Diaper,Meat,Pencil,Wine}"
## [422] "{Bread,Diaper,Milk,Pencil}"
## [423] "{Diaper,Eggs,Milk,Pencil}"
## [424] "{Bagel,Bread,Diaper,Pencil}"
## [425] "{Bagel,Bread}"
## [426] "{Bagel,Milk}"
## [427] "{Cheese,Eggs,Meat}"
## [428] "{Bagel,Bread,Cheese,Meat,Milk,Wine}"
## [429] "{Bread,Diaper,Eggs,Pencil,Wine}"
## [430] "{Bagel,Cheese,Diaper,Milk,Wine}"
## [431] "{Bread,Cheese,Diaper,Milk,Pencil}"
## [432] "{Bagel,Diaper,Milk,Pencil}"
## [433] "{Bread,Cheese,Diaper,Meat,Milk,Wine}"
## [434] "{Bagel,Bread,Diaper,Meat,Wine}"
## [435] "{Bread,Diaper,Eggs,Milk,Pencil}"
## [436] "{Bagel,Bread,Diaper,Eggs,Milk,Wine}"
## [437] "{Bagel,Cheese,Milk,Pencil,Wine}"
## [438] "{Cheese,Eggs,Meat,Milk}"
## [439] "{Bagel,Bread,Cheese,Diaper,Meat}"
## [440] "{Bagel,Bread,Eggs,Meat,Wine}"
## [441] "{Cheese,Diaper,Milk,Pencil,Wine}"
## [442] "{Bagel,Bread,Cheese,Eggs,Pencil}"
## [443] "{Bread,Cheese,Diaper,Eggs,Milk,Wine}"
## [444] "{Bread,Cheese,Diaper,Meat,Pencil,Wine}"
## [445] "{Cheese,Eggs,Meat,Milk,Wine}"
## [446] "{Bagel,Bread,Eggs,Milk,Pencil,Wine}"
## [447] "{Bagel,Bread,Milk}"
## [448] "{Bagel,Bread,Diaper,Meat,Pencil}"
## Itemsets in Consequent (RHS)
## [1] "{Milk}" "{Bagel}" "{Meat}" "{Diaper}" "{Eggs}" "{Bread}" "{Cheese}"
## [8] "{Pencil}" "{Wine}"
plot(datarules, shading="order", control=list(main="Two-key plot"))## To reduce overplotting, jitter is added! Use jitter = 0 to prevent jitter.
plot(datarules, method="grouped") 
plot(rules.wine, method="grouped")
Graphs
plot(datarules, method="graph", control=list(type="items"))## Warning: Unknown control parameters: type## Available control parameters (with default values):
## layout = stress
## circular = FALSE
## ggraphdots = NULL
## edges = <environment>
## nodes = <environment>
## nodetext = <environment>
## colors = c("#EE0000FF", "#EEEEEEFF")
## engine = ggplot2
## max = 100
## verbose = FALSE## Warning: Too many rules supplied. Only plotting the best 100 using
## 'lift' (change control parameter max if needed).
Although, the main part was done successfully imppemented, I would like to try some other plots too.
You will see the results next.
plot(datarules, method="paracoord", control=list(reorder=TRUE))
This plot will allow to compare the feature of several individual observations on a set of variables. From here we can see that each data set is represented as a point on this graph. As a line connecting corresponding values on the axis. The point of intersection on axis corresponds to the value the variable has in that dimension. With this plot we can see direct and inverse relationships between data points and multiple variables.
For example we can see that lines from 6 to 5 are almost parallel, meaning that they have positive relationship. If not, then it means that there is negative relationship, meaning that when buying one product people usually avoid buying the other one.
I understand that my knowledge of coding is not broad, but I tried multiple times to make it so that the name of products would be below or above and positions on the y axis, since I think that, that would be a better option to analyze our data, in relation to each other, however, I was not able to do that.
I was desperately trying to do this plot, since in my humble opinion this is the best way to visualize the relations between our products.
And in my opinion it is the best way to plot, since we can directly change the way our shop is designed. By this I mean that we can plot it in a way to see the relationships, and put the products as bundles, or together in order to kind if appeal the customers. It would make the shop more profitable, since we saw thta people who buy wine as positively related to buying cheese, and that means that we
Using the ECLAT algorithm
freq.items<-eclat(data, parameter=list(supp=0.006, maxlen=15)) ## Eclat
##
## parameter specification:
## tidLists support minlen maxlen target ext
## FALSE 0.006 1 15 frequent itemsets TRUE
##
## algorithmic control:
## sparse sort verbose
## 7 -2 TRUE
##
## Absolute minimum support count: 1
##
## create itemset ...
## set transactions ...[9 item(s), 315 transaction(s)] done [0.00s].
## sorting and recoding items ... [9 item(s)] done [0.00s].
## creating bit matrix ... [9 row(s), 315 column(s)] done [0.00s].
## writing ... [471 set(s)] done [0.00s].
## Creating S4 object ... done [0.00s].inspect(freq.items)## items support count
## [1] {Bagel, Cheese, Diaper, Eggs, Meat, Pencil, Wine} 0.012698413 4
## [2] {Bagel, Bread, Cheese, Diaper, Eggs, Pencil, Wine} 0.006349206 2
## [3] {Bagel, Cheese, Diaper, Eggs, Pencil, Wine} 0.019047619 6
## [4] {Bagel, Bread, Diaper, Eggs, Pencil, Wine} 0.009523810 3
## [5] {Bagel, Diaper, Eggs, Meat, Pencil, Wine} 0.012698413 4
## [6] {Bagel, Bread, Diaper, Eggs, Meat, Milk, Pencil} 0.006349206 2
## [7] {Bagel, Cheese, Diaper, Eggs, Meat, Pencil} 0.012698413 4
## [8] {Bagel, Bread, Diaper, Eggs, Meat, Pencil} 0.006349206 2
## [9] {Bagel, Diaper, Eggs, Meat, Milk, Pencil} 0.006349206 2
## [10] {Bagel, Bread, Diaper, Eggs, Milk, Pencil} 0.009523810 3
## [11] {Bagel, Bread, Cheese, Diaper, Eggs, Pencil} 0.006349206 2
## [12] {Bagel, Cheese, Diaper, Eggs, Pencil} 0.019047619 6
## [13] {Bagel, Bread, Diaper, Eggs, Pencil} 0.015873016 5
## [14] {Bagel, Diaper, Eggs, Milk, Pencil} 0.009523810 3
## [15] {Bagel, Diaper, Eggs, Meat, Pencil} 0.019047619 6
## [16] {Bagel, Diaper, Eggs, Pencil, Wine} 0.025396825 8
## [17] {Bagel, Bread, Cheese, Diaper, Meat, Pencil, Wine} 0.006349206 2
## [18] {Bagel, Cheese, Diaper, Meat, Pencil, Wine} 0.019047619 6
## [19] {Bagel, Bread, Diaper, Meat, Pencil, Wine} 0.006349206 2
## [20] {Bagel, Cheese, Diaper, Milk, Pencil, Wine} 0.006349206 2
## [21] {Bagel, Bread, Cheese, Diaper, Pencil, Wine} 0.012698413 4
## [22] {Bagel, Cheese, Diaper, Pencil, Wine} 0.031746032 10
## [23] {Bagel, Bread, Diaper, Pencil, Wine} 0.015873016 5
## [24] {Bagel, Diaper, Milk, Pencil, Wine} 0.009523810 3
## [25] {Bagel, Diaper, Meat, Pencil, Wine} 0.022222222 7
## [26] {Bagel, Bread, Diaper, Meat, Milk, Pencil} 0.006349206 2
## [27] {Bagel, Bread, Cheese, Diaper, Meat, Pencil} 0.012698413 4
## [28] {Bagel, Cheese, Diaper, Meat, Pencil} 0.025396825 8
## [29] {Bagel, Bread, Diaper, Meat, Pencil} 0.025396825 8
## [30] {Bagel, Diaper, Meat, Milk, Pencil} 0.009523810 3
## [31] {Bagel, Cheese, Diaper, Milk, Pencil} 0.009523810 3
## [32] {Bagel, Bread, Diaper, Milk, Pencil} 0.019047619 6
## [33] {Bagel, Bread, Cheese, Diaper, Pencil} 0.025396825 8
## [34] {Bagel, Cheese, Diaper, Pencil} 0.044444444 14
## [35] {Bagel, Bread, Diaper, Pencil} 0.047619048 15
## [36] {Bagel, Diaper, Milk, Pencil} 0.028571429 9
## [37] {Bagel, Diaper, Meat, Pencil} 0.044444444 14
## [38] {Bagel, Diaper, Pencil, Wine} 0.041269841 13
## [39] {Bagel, Diaper, Eggs, Pencil} 0.031746032 10
## [40] {Bread, Cheese, Diaper, Eggs, Meat, Pencil, Wine} 0.009523810 3
## [41] {Cheese, Diaper, Eggs, Meat, Pencil, Wine} 0.022222222 7
## [42] {Bread, Diaper, Eggs, Meat, Pencil, Wine} 0.009523810 3
## [43] {Cheese, Diaper, Eggs, Milk, Pencil, Wine} 0.006349206 2
## [44] {Bread, Diaper, Eggs, Milk, Pencil, Wine} 0.006349206 2
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## [357] {Bagel, Eggs, Milk, Wine} 0.047619048 15
## [358] {Bagel, Eggs, Meat, Wine} 0.057142857 18
## [359] {Bagel, Cheese, Eggs, Meat, Milk} 0.019047619 6
## [360] {Bagel, Bread, Eggs, Meat, Milk} 0.022222222 7
## [361] {Bagel, Bread, Cheese, Eggs, Meat} 0.019047619 6
## [362] {Bagel, Cheese, Eggs, Meat} 0.063492063 20
## [363] {Bagel, Bread, Eggs, Meat} 0.044444444 14
## [364] {Bagel, Eggs, Meat, Milk} 0.041269841 13
## [365] {Bagel, Bread, Cheese, Eggs, Milk} 0.015873016 5
## [366] {Bagel, Cheese, Eggs, Milk} 0.031746032 10
## [367] {Bagel, Bread, Eggs, Milk} 0.041269841 13
## [368] {Bagel, Bread, Cheese, Eggs} 0.044444444 14
## [369] {Bagel, Cheese, Eggs} 0.092063492 29
## [370] {Bagel, Bread, Eggs} 0.085714286 27
## [371] {Bagel, Eggs, Milk} 0.063492063 20
## [372] {Bagel, Eggs, Meat} 0.092063492 29
## [373] {Bagel, Eggs, Wine} 0.092063492 29
## [374] {Bagel, Bread, Cheese, Meat, Milk, Wine} 0.019047619 6
## [375] {Bagel, Cheese, Meat, Milk, Wine} 0.028571429 9
## [376] {Bagel, Bread, Meat, Milk, Wine} 0.031746032 10
## [377] {Bagel, Bread, Cheese, Meat, Wine} 0.031746032 10
## [378] {Bagel, Cheese, Meat, Wine} 0.063492063 20
## [379] {Bagel, Bread, Meat, Wine} 0.060317460 19
## [380] {Bagel, Meat, Milk, Wine} 0.044444444 14
## [381] {Bagel, Bread, Cheese, Milk, Wine} 0.031746032 10
## [382] {Bagel, Cheese, Milk, Wine} 0.057142857 18
## [383] {Bagel, Bread, Milk, Wine} 0.057142857 18
## [384] {Bagel, Bread, Cheese, Wine} 0.057142857 18
## [385] {Bagel, Cheese, Wine} 0.107936508 34
## [386] {Bagel, Bread, Wine} 0.101587302 32
## [387] {Bagel, Milk, Wine} 0.088888889 28
## [388] {Bagel, Meat, Wine} 0.104761905 33
## [389] {Bagel, Bread, Cheese, Meat, Milk} 0.028571429 9
## [390] {Bagel, Cheese, Meat, Milk} 0.050793651 16
## [391] {Bagel, Bread, Meat, Milk} 0.047619048 15
## [392] {Bagel, Bread, Cheese, Meat} 0.066666667 21
## [393] {Bagel, Cheese, Meat} 0.120634921 38
## [394] {Bagel, Bread, Meat} 0.114285714 36
## [395] {Bagel, Meat, Milk} 0.076190476 24
## [396] {Bagel, Bread, Cheese, Milk} 0.044444444 14
## [397] {Bagel, Cheese, Milk} 0.088888889 28
## [398] {Bagel, Bread, Milk} 0.171428571 54
## [399] {Bagel, Bread, Cheese} 0.104761905 33
## [400] {Bagel, Cheese} 0.193650794 61
## [401] {Bagel, Bread} 0.279365079 88
## [402] {Bagel, Milk} 0.225396825 71
## [403] {Bagel, Meat} 0.190476190 60
## [404] {Bagel, Wine} 0.171428571 54
## [405] {Bagel, Eggs} 0.152380952 48
## [406] {Bread, Cheese, Eggs, Meat, Milk, Wine} 0.025396825 8
## [407] {Cheese, Eggs, Meat, Milk, Wine} 0.073015873 23
## [408] {Bread, Eggs, Meat, Milk, Wine} 0.041269841 13
## [409] {Bread, Cheese, Eggs, Meat, Wine} 0.041269841 13
## [410] {Cheese, Eggs, Meat, Wine} 0.111111111 35
## [411] {Bread, Eggs, Meat, Wine} 0.063492063 20
## [412] {Eggs, Meat, Milk, Wine} 0.092063492 29
## [413] {Bread, Cheese, Eggs, Milk, Wine} 0.050793651 16
## [414] {Cheese, Eggs, Milk, Wine} 0.104761905 33
## [415] {Bread, Eggs, Milk, Wine} 0.076190476 24
## [416] {Bread, Cheese, Eggs, Wine} 0.073015873 23
## [417] {Cheese, Eggs, Wine} 0.165079365 52
## [418] {Bread, Eggs, Wine} 0.120634921 38
## [419] {Eggs, Milk, Wine} 0.136507937 43
## [420] {Eggs, Meat, Wine} 0.149206349 47
## [421] {Bread, Cheese, Eggs, Meat, Milk} 0.038095238 12
## [422] {Cheese, Eggs, Meat, Milk} 0.152380952 48
## [423] {Bread, Eggs, Meat, Milk} 0.060317460 19
## [424] {Bread, Cheese, Eggs, Meat} 0.063492063 20
## [425] {Cheese, Eggs, Meat} 0.215873016 68
## [426] {Bread, Eggs, Meat} 0.092063492 29
## [427] {Eggs, Meat, Milk} 0.177777778 56
## [428] {Bread, Cheese, Eggs, Milk} 0.073015873 23
## [429] {Cheese, Eggs, Milk} 0.196825397 62
## [430] {Bread, Eggs, Milk} 0.104761905 33
## [431] {Bread, Cheese, Eggs} 0.117460317 37
## [432] {Cheese, Eggs} 0.298412698 94
## [433] {Bread, Eggs} 0.187301587 59
## [434] {Eggs, Milk} 0.244444444 77
## [435] {Eggs, Meat} 0.266666667 84
## [436] {Eggs, Wine} 0.241269841 76
## [437] {Bread, Cheese, Meat, Milk, Wine} 0.053968254 17
## [438] {Cheese, Meat, Milk, Wine} 0.101587302 32
## [439] {Bread, Meat, Milk, Wine} 0.076190476 24
## [440] {Bread, Cheese, Meat, Wine} 0.088888889 28
## [441] {Cheese, Meat, Wine} 0.168253968 53
## [442] {Bread, Meat, Wine} 0.133333333 42
## [443] {Meat, Milk, Wine} 0.126984127 40
## [444] {Bread, Cheese, Milk, Wine} 0.085714286 27
## [445] {Cheese, Milk, Wine} 0.161904762 51
## [446] {Bread, Milk, Wine} 0.130158730 41
## [447] {Bread, Cheese, Wine} 0.142857143 45
## [448] {Cheese, Wine} 0.269841270 85
## [449] {Bread, Wine} 0.244444444 77
## [450] {Milk, Wine} 0.219047619 69
## [451] {Meat, Wine} 0.250793651 79
## [452] {Bread, Cheese, Meat, Milk} 0.076190476 24
## [453] {Cheese, Meat, Milk} 0.203174603 64
## [454] {Bread, Meat, Milk} 0.104761905 33
## [455] {Bread, Cheese, Meat} 0.142857143 45
## [456] {Cheese, Meat} 0.323809524 102
## [457] {Bread, Meat} 0.206349206 65
## [458] {Meat, Milk} 0.244444444 77
## [459] {Bread, Cheese, Milk} 0.130158730 41
## [460] {Cheese, Milk} 0.304761905 96
## [461] {Bread, Milk} 0.279365079 88
## [462] {Bread, Cheese} 0.238095238 75
## [463] {Cheese} 0.501587302 158
## [464] {Bread} 0.504761905 159
## [465] {Milk} 0.501587302 158
## [466] {Meat} 0.476190476 150
## [467] {Wine} 0.438095238 138
## [468] {Eggs} 0.438095238 138
## [469] {Bagel} 0.425396825 134
## [470] {Diaper} 0.406349206 128
## [471] {Pencil} 0.361904762 114Basic statistics with reference to confidence
freq.rules<-ruleInduction(freq.items, data, confidence=0.5)
freq.rules## set of 1096 rulesfreq.items<-eclat(data, parameter=list(supp=0.05, maxlen=15)) ## Eclat
##
## parameter specification:
## tidLists support minlen maxlen target ext
## FALSE 0.05 1 15 frequent itemsets TRUE
##
## algorithmic control:
## sparse sort verbose
## 7 -2 TRUE
##
## Absolute minimum support count: 15
##
## create itemset ...
## set transactions ...[9 item(s), 315 transaction(s)] done [0.00s].
## sorting and recoding items ... [9 item(s)] done [0.00s].
## creating bit matrix ... [9 row(s), 315 column(s)] done [0.00s].
## writing ... [209 set(s)] done [0.00s].
## Creating S4 object ... done [0.00s].inspect(freq.items)## items support count
## [1] {Diaper, Eggs, Pencil, Wine} 0.06349206 20
## [2] {Cheese, Diaper, Pencil, Wine} 0.06349206 20
## [3] {Bread, Diaper, Pencil, Wine} 0.05714286 18
## [4] {Diaper, Meat, Pencil, Wine} 0.06031746 19
## [5] {Bread, Diaper, Meat, Pencil} 0.05714286 18
## [6] {Bread, Diaper, Milk, Pencil} 0.05079365 16
## [7] {Bread, Cheese, Diaper, Pencil} 0.05714286 18
## [8] {Cheese, Diaper, Pencil} 0.08888889 28
## [9] {Bread, Diaper, Pencil} 0.10476190 33
## [10] {Diaper, Milk, Pencil} 0.07301587 23
## [11] {Diaper, Meat, Pencil} 0.08253968 26
## [12] {Diaper, Pencil, Wine} 0.10793651 34
## [13] {Diaper, Eggs, Pencil} 0.08253968 26
## [14] {Bagel, Diaper, Pencil} 0.08253968 26
## [15] {Bagel, Eggs, Pencil, Wine} 0.05079365 16
## [16] {Bagel, Cheese, Pencil, Wine} 0.05396825 17
## [17] {Bagel, Bread, Cheese, Pencil} 0.05396825 17
## [18] {Bagel, Cheese, Pencil} 0.08888889 28
## [19] {Bagel, Bread, Pencil} 0.08888889 28
## [20] {Bagel, Milk, Pencil} 0.06984127 22
## [21] {Bagel, Meat, Pencil} 0.08571429 27
## [22] {Bagel, Pencil, Wine} 0.08253968 26
## [23] {Bagel, Eggs, Pencil} 0.07301587 23
## [24] {Cheese, Eggs, Pencil, Wine} 0.08571429 27
## [25] {Bread, Eggs, Pencil, Wine} 0.06666667 21
## [26] {Eggs, Milk, Pencil, Wine} 0.05714286 18
## [27] {Eggs, Meat, Pencil, Wine} 0.06031746 19
## [28] {Cheese, Eggs, Meat, Pencil} 0.05396825 17
## [29] {Cheese, Eggs, Milk, Pencil} 0.05079365 16
## [30] {Bread, Eggs, Milk, Pencil} 0.06349206 20
## [31] {Bread, Cheese, Eggs, Pencil} 0.06666667 21
## [32] {Cheese, Eggs, Pencil} 0.10793651 34
## [33] {Bread, Eggs, Pencil} 0.09841270 31
## [34] {Eggs, Milk, Pencil} 0.08571429 27
## [35] {Eggs, Meat, Pencil} 0.07936508 25
## [36] {Eggs, Pencil, Wine} 0.12063492 38
## [37] {Bread, Cheese, Meat, Pencil, Wine} 0.05396825 17
## [38] {Cheese, Meat, Pencil, Wine} 0.07301587 23
## [39] {Bread, Meat, Pencil, Wine} 0.07301587 23
## [40] {Meat, Milk, Pencil, Wine} 0.05079365 16
## [41] {Cheese, Milk, Pencil, Wine} 0.06349206 20
## [42] {Bread, Milk, Pencil, Wine} 0.07301587 23
## [43] {Bread, Cheese, Pencil, Wine} 0.07301587 23
## [44] {Cheese, Pencil, Wine} 0.12698413 40
## [45] {Bread, Pencil, Wine} 0.11428571 36
## [46] {Milk, Pencil, Wine} 0.09523810 30
## [47] {Meat, Pencil, Wine} 0.11428571 36
## [48] {Bread, Meat, Milk, Pencil} 0.05714286 18
## [49] {Bread, Cheese, Meat, Pencil} 0.07936508 25
## [50] {Cheese, Meat, Pencil} 0.10476190 33
## [51] {Bread, Meat, Pencil} 0.11111111 35
## [52] {Meat, Milk, Pencil} 0.07936508 25
## [53] {Bread, Cheese, Milk, Pencil} 0.06349206 20
## [54] {Cheese, Milk, Pencil} 0.10158730 32
## [55] {Bread, Milk, Pencil} 0.10793651 34
## [56] {Bread, Cheese, Pencil} 0.12380952 39
## [57] {Cheese, Pencil} 0.20000000 63
## [58] {Bread, Pencil} 0.20000000 63
## [59] {Milk, Pencil} 0.17142857 54
## [60] {Meat, Pencil} 0.17777778 56
## [61] {Pencil, Wine} 0.20000000 63
## [62] {Eggs, Pencil} 0.16507937 52
## [63] {Bagel, Pencil} 0.15873016 50
## [64] {Diaper, Pencil} 0.17142857 54
## [65] {Bagel, Cheese, Diaper, Eggs} 0.05079365 16
## [66] {Bagel, Diaper, Eggs, Meat} 0.05079365 16
## [67] {Bagel, Cheese, Diaper, Wine} 0.06666667 21
## [68] {Bagel, Bread, Diaper, Wine} 0.06349206 20
## [69] {Bagel, Diaper, Meat, Wine} 0.05396825 17
## [70] {Bagel, Cheese, Diaper, Meat} 0.06984127 22
## [71] {Bagel, Bread, Diaper, Meat} 0.06984127 22
## [72] {Bagel, Bread, Diaper, Milk} 0.05714286 18
## [73] {Bagel, Bread, Cheese, Diaper} 0.06666667 21
## [74] {Bagel, Cheese, Diaper} 0.10793651 34
## [75] {Bagel, Bread, Diaper} 0.12063492 38
## [76] {Bagel, Diaper, Milk} 0.07936508 25
## [77] {Bagel, Diaper, Meat} 0.10476190 33
## [78] {Bagel, Diaper, Wine} 0.10158730 32
## [79] {Bagel, Diaper, Eggs} 0.06984127 22
## [80] {Cheese, Diaper, Eggs, Wine} 0.06984127 22
## [81] {Bread, Diaper, Eggs, Wine} 0.06349206 20
## [82] {Diaper, Eggs, Meat, Wine} 0.05714286 18
## [83] {Cheese, Diaper, Eggs, Meat} 0.06031746 19
## [84] {Bread, Diaper, Eggs, Milk} 0.05079365 16
## [85] {Bread, Cheese, Diaper, Eggs} 0.05714286 18
## [86] {Cheese, Diaper, Eggs} 0.10158730 32
## [87] {Bread, Diaper, Eggs} 0.08888889 28
## [88] {Diaper, Eggs, Milk} 0.07301587 23
## [89] {Diaper, Eggs, Meat} 0.08571429 27
## [90] {Diaper, Eggs, Wine} 0.11111111 35
## [91] {Cheese, Diaper, Meat, Wine} 0.07301587 23
## [92] {Bread, Diaper, Meat, Wine} 0.07619048 24
## [93] {Cheese, Diaper, Milk, Wine} 0.06666667 21
## [94] {Bread, Diaper, Milk, Wine} 0.06666667 21
## [95] {Bread, Cheese, Diaper, Wine} 0.08571429 27
## [96] {Cheese, Diaper, Wine} 0.13650794 43
## [97] {Bread, Diaper, Wine} 0.14920635 47
## [98] {Diaper, Milk, Wine} 0.09206349 29
## [99] {Diaper, Meat, Wine} 0.12380952 39
## [100] {Bread, Diaper, Meat, Milk} 0.05396825 17
## [101] {Bread, Cheese, Diaper, Meat} 0.07936508 25
## [102] {Cheese, Diaper, Meat} 0.11428571 36
## [103] {Bread, Diaper, Meat} 0.12063492 38
## [104] {Diaper, Meat, Milk} 0.06349206 20
## [105] {Bread, Cheese, Diaper, Milk} 0.06666667 21
## [106] {Cheese, Diaper, Milk} 0.09523810 30
## [107] {Bread, Diaper, Milk} 0.11428571 36
## [108] {Bread, Cheese, Diaper} 0.13650794 43
## [109] {Cheese, Diaper} 0.20000000 63
## [110] {Bread, Diaper} 0.23174603 73
## [111] {Diaper, Milk} 0.15555556 49
## [112] {Diaper, Meat} 0.19365079 61
## [113] {Diaper, Wine} 0.23492063 74
## [114] {Diaper, Eggs} 0.16190476 51
## [115] {Bagel, Diaper} 0.18412698 58
## [116] {Bagel, Cheese, Eggs, Wine} 0.05714286 18
## [117] {Bagel, Bread, Eggs, Wine} 0.05079365 16
## [118] {Bagel, Eggs, Meat, Wine} 0.05714286 18
## [119] {Bagel, Cheese, Eggs, Meat} 0.06349206 20
## [120] {Bagel, Cheese, Eggs} 0.09206349 29
## [121] {Bagel, Bread, Eggs} 0.08571429 27
## [122] {Bagel, Eggs, Milk} 0.06349206 20
## [123] {Bagel, Eggs, Meat} 0.09206349 29
## [124] {Bagel, Eggs, Wine} 0.09206349 29
## [125] {Bagel, Cheese, Meat, Wine} 0.06349206 20
## [126] {Bagel, Bread, Meat, Wine} 0.06031746 19
## [127] {Bagel, Cheese, Milk, Wine} 0.05714286 18
## [128] {Bagel, Bread, Milk, Wine} 0.05714286 18
## [129] {Bagel, Bread, Cheese, Wine} 0.05714286 18
## [130] {Bagel, Cheese, Wine} 0.10793651 34
## [131] {Bagel, Bread, Wine} 0.10158730 32
## [132] {Bagel, Milk, Wine} 0.08888889 28
## [133] {Bagel, Meat, Wine} 0.10476190 33
## [134] {Bagel, Cheese, Meat, Milk} 0.05079365 16
## [135] {Bagel, Bread, Cheese, Meat} 0.06666667 21
## [136] {Bagel, Cheese, Meat} 0.12063492 38
## [137] {Bagel, Bread, Meat} 0.11428571 36
## [138] {Bagel, Meat, Milk} 0.07619048 24
## [139] {Bagel, Cheese, Milk} 0.08888889 28
## [140] {Bagel, Bread, Milk} 0.17142857 54
## [141] {Bagel, Bread, Cheese} 0.10476190 33
## [142] {Bagel, Cheese} 0.19365079 61
## [143] {Bagel, Bread} 0.27936508 88
## [144] {Bagel, Milk} 0.22539683 71
## [145] {Bagel, Meat} 0.19047619 60
## [146] {Bagel, Wine} 0.17142857 54
## [147] {Bagel, Eggs} 0.15238095 48
## [148] {Cheese, Eggs, Meat, Milk, Wine} 0.07301587 23
## [149] {Cheese, Eggs, Meat, Wine} 0.11111111 35
## [150] {Bread, Eggs, Meat, Wine} 0.06349206 20
## [151] {Eggs, Meat, Milk, Wine} 0.09206349 29
## [152] {Bread, Cheese, Eggs, Milk, Wine} 0.05079365 16
## [153] {Cheese, Eggs, Milk, Wine} 0.10476190 33
## [154] {Bread, Eggs, Milk, Wine} 0.07619048 24
## [155] {Bread, Cheese, Eggs, Wine} 0.07301587 23
## [156] {Cheese, Eggs, Wine} 0.16507937 52
## [157] {Bread, Eggs, Wine} 0.12063492 38
## [158] {Eggs, Milk, Wine} 0.13650794 43
## [159] {Eggs, Meat, Wine} 0.14920635 47
## [160] {Cheese, Eggs, Meat, Milk} 0.15238095 48
## [161] {Bread, Eggs, Meat, Milk} 0.06031746 19
## [162] {Bread, Cheese, Eggs, Meat} 0.06349206 20
## [163] {Cheese, Eggs, Meat} 0.21587302 68
## [164] {Bread, Eggs, Meat} 0.09206349 29
## [165] {Eggs, Meat, Milk} 0.17777778 56
## [166] {Bread, Cheese, Eggs, Milk} 0.07301587 23
## [167] {Cheese, Eggs, Milk} 0.19682540 62
## [168] {Bread, Eggs, Milk} 0.10476190 33
## [169] {Bread, Cheese, Eggs} 0.11746032 37
## [170] {Cheese, Eggs} 0.29841270 94
## [171] {Bread, Eggs} 0.18730159 59
## [172] {Eggs, Milk} 0.24444444 77
## [173] {Eggs, Meat} 0.26666667 84
## [174] {Eggs, Wine} 0.24126984 76
## [175] {Bread, Cheese, Meat, Milk, Wine} 0.05396825 17
## [176] {Cheese, Meat, Milk, Wine} 0.10158730 32
## [177] {Bread, Meat, Milk, Wine} 0.07619048 24
## [178] {Bread, Cheese, Meat, Wine} 0.08888889 28
## [179] {Cheese, Meat, Wine} 0.16825397 53
## [180] {Bread, Meat, Wine} 0.13333333 42
## [181] {Meat, Milk, Wine} 0.12698413 40
## [182] {Bread, Cheese, Milk, Wine} 0.08571429 27
## [183] {Cheese, Milk, Wine} 0.16190476 51
## [184] {Bread, Milk, Wine} 0.13015873 41
## [185] {Bread, Cheese, Wine} 0.14285714 45
## [186] {Cheese, Wine} 0.26984127 85
## [187] {Bread, Wine} 0.24444444 77
## [188] {Milk, Wine} 0.21904762 69
## [189] {Meat, Wine} 0.25079365 79
## [190] {Bread, Cheese, Meat, Milk} 0.07619048 24
## [191] {Cheese, Meat, Milk} 0.20317460 64
## [192] {Bread, Meat, Milk} 0.10476190 33
## [193] {Bread, Cheese, Meat} 0.14285714 45
## [194] {Cheese, Meat} 0.32380952 102
## [195] {Bread, Meat} 0.20634921 65
## [196] {Meat, Milk} 0.24444444 77
## [197] {Bread, Cheese, Milk} 0.13015873 41
## [198] {Cheese, Milk} 0.30476190 96
## [199] {Bread, Milk} 0.27936508 88
## [200] {Bread, Cheese} 0.23809524 75
## [201] {Cheese} 0.50158730 158
## [202] {Bread} 0.50476190 159
## [203] {Milk} 0.50158730 158
## [204] {Meat} 0.47619048 150
## [205] {Wine} 0.43809524 138
## [206] {Eggs} 0.43809524 138
## [207] {Bagel} 0.42539683 134
## [208] {Diaper} 0.40634921 128
## [209] {Pencil} 0.36190476 114freq.rules<-ruleInduction(freq.items, data, confidence=0.1)
freq.rules## set of 648 rulesinspect(freq.rules)## lhs rhs support confidence lift
## [1] {Eggs, Pencil, Wine} => {Diaper} 0.06349206 0.5263158 1.2952303
## [2] {Diaper, Pencil, Wine} => {Eggs} 0.06349206 0.5882353 1.3427110
## [3] {Diaper, Eggs, Wine} => {Pencil} 0.06349206 0.5714286 1.5789474
## [4] {Diaper, Eggs, Pencil} => {Wine} 0.06349206 0.7692308 1.7558528
## [5] {Diaper, Pencil, Wine} => {Cheese} 0.06349206 0.5882353 1.1727476
## [6] {Cheese, Pencil, Wine} => {Diaper} 0.06349206 0.5000000 1.2304688
## [7] {Cheese, Diaper, Wine} => {Pencil} 0.06349206 0.4651163 1.2851897
## [8] {Cheese, Diaper, Pencil} => {Wine} 0.06349206 0.7142857 1.6304348
## [9] {Diaper, Pencil, Wine} => {Bread} 0.05714286 0.5294118 1.0488346
## [10] {Bread, Pencil, Wine} => {Diaper} 0.05714286 0.5000000 1.2304688
## [11] {Bread, Diaper, Wine} => {Pencil} 0.05714286 0.3829787 1.0582307
## [12] {Bread, Diaper, Pencil} => {Wine} 0.05714286 0.5454545 1.2450593
## [13] {Meat, Pencil, Wine} => {Diaper} 0.06031746 0.5277778 1.2988281
## [14] {Diaper, Pencil, Wine} => {Meat} 0.06031746 0.5588235 1.1735294
## [15] {Diaper, Meat, Wine} => {Pencil} 0.06031746 0.4871795 1.3461538
## [16] {Diaper, Meat, Pencil} => {Wine} 0.06031746 0.7307692 1.6680602
## [17] {Diaper, Meat, Pencil} => {Bread} 0.05714286 0.6923077 1.3715530
## [18] {Bread, Meat, Pencil} => {Diaper} 0.05714286 0.5142857 1.2656250
## [19] {Bread, Diaper, Pencil} => {Meat} 0.05714286 0.5454545 1.1454545
## [20] {Bread, Diaper, Meat} => {Pencil} 0.05714286 0.4736842 1.3088643
## [21] {Diaper, Milk, Pencil} => {Bread} 0.05079365 0.6956522 1.3781788
## [22] {Bread, Milk, Pencil} => {Diaper} 0.05079365 0.4705882 1.1580882
## [23] {Bread, Diaper, Pencil} => {Milk} 0.05079365 0.4848485 0.9666283
## [24] {Bread, Diaper, Milk} => {Pencil} 0.05079365 0.4444444 1.2280702
## [25] {Cheese, Diaper, Pencil} => {Bread} 0.05714286 0.6428571 1.2735849
## [26] {Bread, Diaper, Pencil} => {Cheese} 0.05714286 0.5454545 1.0874568
## [27] {Bread, Cheese, Pencil} => {Diaper} 0.05714286 0.4615385 1.1358173
## [28] {Bread, Cheese, Diaper} => {Pencil} 0.05714286 0.4186047 1.1566707
## [29] {Diaper, Pencil} => {Cheese} 0.08888889 0.5185185 1.0337553
## [30] {Cheese, Pencil} => {Diaper} 0.08888889 0.4444444 1.0937500
## [31] {Cheese, Diaper} => {Pencil} 0.08888889 0.4444444 1.2280702
## [32] {Diaper, Pencil} => {Bread} 0.10476190 0.6111111 1.2106918
## [33] {Bread, Pencil} => {Diaper} 0.10476190 0.5238095 1.2890625
## [34] {Bread, Diaper} => {Pencil} 0.10476190 0.4520548 1.2490988
## [35] {Milk, Pencil} => {Diaper} 0.07301587 0.4259259 1.0481771
## [36] {Diaper, Pencil} => {Milk} 0.07301587 0.4259259 0.8491561
## [37] {Diaper, Milk} => {Pencil} 0.07301587 0.4693878 1.2969925
## [38] {Meat, Pencil} => {Diaper} 0.08253968 0.4642857 1.1425781
## [39] {Diaper, Pencil} => {Meat} 0.08253968 0.4814815 1.0111111
## [40] {Diaper, Meat} => {Pencil} 0.08253968 0.4262295 1.1777394
## [41] {Pencil, Wine} => {Diaper} 0.10793651 0.5396825 1.3281250
## [42] {Diaper, Wine} => {Pencil} 0.10793651 0.4594595 1.2695590
## [43] {Diaper, Pencil} => {Wine} 0.10793651 0.6296296 1.4371981
## [44] {Eggs, Pencil} => {Diaper} 0.08253968 0.5000000 1.2304688
## [45] {Diaper, Pencil} => {Eggs} 0.08253968 0.4814815 1.0990338
## [46] {Diaper, Eggs} => {Pencil} 0.08253968 0.5098039 1.4086687
## [47] {Diaper, Pencil} => {Bagel} 0.08253968 0.4814815 1.1318408
## [48] {Bagel, Pencil} => {Diaper} 0.08253968 0.5200000 1.2796875
## [49] {Bagel, Diaper} => {Pencil} 0.08253968 0.4482759 1.2386570
## [50] {Eggs, Pencil, Wine} => {Bagel} 0.05079365 0.4210526 0.9897879
## [51] {Bagel, Pencil, Wine} => {Eggs} 0.05079365 0.6153846 1.4046823
## [52] {Bagel, Eggs, Wine} => {Pencil} 0.05079365 0.5517241 1.5245009
## [53] {Bagel, Eggs, Pencil} => {Wine} 0.05079365 0.6956522 1.5879017
## [54] {Cheese, Pencil, Wine} => {Bagel} 0.05396825 0.4250000 0.9990672
## [55] {Bagel, Pencil, Wine} => {Cheese} 0.05396825 0.6538462 1.3035540
## [56] {Bagel, Cheese, Wine} => {Pencil} 0.05396825 0.5000000 1.3815789
## [57] {Bagel, Cheese, Pencil} => {Wine} 0.05396825 0.6071429 1.3858696
## [58] {Bread, Cheese, Pencil} => {Bagel} 0.05396825 0.4358974 1.0246843
## [59] {Bagel, Cheese, Pencil} => {Bread} 0.05396825 0.6071429 1.2028302
## [60] {Bagel, Bread, Pencil} => {Cheese} 0.05396825 0.6071429 1.2104430
## [61] {Bagel, Bread, Cheese} => {Pencil} 0.05396825 0.5151515 1.4234450
## [62] {Cheese, Pencil} => {Bagel} 0.08888889 0.4444444 1.0447761
## [63] {Bagel, Pencil} => {Cheese} 0.08888889 0.5600000 1.1164557
## [64] {Bagel, Cheese} => {Pencil} 0.08888889 0.4590164 1.2683348
## [65] {Bread, Pencil} => {Bagel} 0.08888889 0.4444444 1.0447761
## [66] {Bagel, Pencil} => {Bread} 0.08888889 0.5600000 1.1094340
## [67] {Bagel, Bread} => {Pencil} 0.08888889 0.3181818 0.8791866
## [68] {Milk, Pencil} => {Bagel} 0.06984127 0.4074074 0.9577114
## [69] {Bagel, Pencil} => {Milk} 0.06984127 0.4400000 0.8772152
## [70] {Bagel, Milk} => {Pencil} 0.06984127 0.3098592 0.8561898
## [71] {Meat, Pencil} => {Bagel} 0.08571429 0.4821429 1.1333955
## [72] {Bagel, Pencil} => {Meat} 0.08571429 0.5400000 1.1340000
## [73] {Bagel, Meat} => {Pencil} 0.08571429 0.4500000 1.2434211
## [74] {Pencil, Wine} => {Bagel} 0.08253968 0.4126984 0.9701493
## [75] {Bagel, Wine} => {Pencil} 0.08253968 0.4814815 1.3304094
## [76] {Bagel, Pencil} => {Wine} 0.08253968 0.5200000 1.1869565
## [77] {Eggs, Pencil} => {Bagel} 0.07301587 0.4423077 1.0397532
## [78] {Bagel, Pencil} => {Eggs} 0.07301587 0.4600000 1.0500000
## [79] {Bagel, Eggs} => {Pencil} 0.07301587 0.4791667 1.3240132
## [80] {Eggs, Pencil, Wine} => {Cheese} 0.08571429 0.7105263 1.4165556
## [81] {Cheese, Pencil, Wine} => {Eggs} 0.08571429 0.6750000 1.5407609
## [82] {Cheese, Eggs, Wine} => {Pencil} 0.08571429 0.5192308 1.4347166
## [83] {Cheese, Eggs, Pencil} => {Wine} 0.08571429 0.7941176 1.8126598
## [84] {Eggs, Pencil, Wine} => {Bread} 0.06666667 0.5526316 1.0948361
## [85] {Bread, Pencil, Wine} => {Eggs} 0.06666667 0.5833333 1.3315217
## [86] {Bread, Eggs, Wine} => {Pencil} 0.06666667 0.5526316 1.5270083
## [87] {Bread, Eggs, Pencil} => {Wine} 0.06666667 0.6774194 1.5462833
## [88] {Milk, Pencil, Wine} => {Eggs} 0.05714286 0.6000000 1.3695652
## [89] {Eggs, Pencil, Wine} => {Milk} 0.05714286 0.4736842 0.9443704
## [90] {Eggs, Milk, Wine} => {Pencil} 0.05714286 0.4186047 1.1566707
## [91] {Eggs, Milk, Pencil} => {Wine} 0.05714286 0.6666667 1.5217391
## [92] {Meat, Pencil, Wine} => {Eggs} 0.06031746 0.5277778 1.2047101
## [93] {Eggs, Pencil, Wine} => {Meat} 0.06031746 0.5000000 1.0500000
## [94] {Eggs, Meat, Wine} => {Pencil} 0.06031746 0.4042553 1.1170213
## [95] {Eggs, Meat, Pencil} => {Wine} 0.06031746 0.7600000 1.7347826
## [96] {Eggs, Meat, Pencil} => {Cheese} 0.05396825 0.6800000 1.3556962
## [97] {Cheese, Meat, Pencil} => {Eggs} 0.05396825 0.5151515 1.1758893
## [98] {Cheese, Eggs, Pencil} => {Meat} 0.05396825 0.5000000 1.0500000
## [99] {Cheese, Eggs, Meat} => {Pencil} 0.05396825 0.2500000 0.6907895
## [100] {Eggs, Milk, Pencil} => {Cheese} 0.05079365 0.5925926 1.1814346
## [101] {Cheese, Milk, Pencil} => {Eggs} 0.05079365 0.5000000 1.1413043
## [102] {Cheese, Eggs, Pencil} => {Milk} 0.05079365 0.4705882 0.9381981
## [103] {Cheese, Eggs, Milk} => {Pencil} 0.05079365 0.2580645 0.7130730
## [104] {Eggs, Milk, Pencil} => {Bread} 0.06349206 0.7407407 1.4675052
## [105] {Bread, Milk, Pencil} => {Eggs} 0.06349206 0.5882353 1.3427110
## [106] {Bread, Eggs, Pencil} => {Milk} 0.06349206 0.6451613 1.2862393
## [107] {Bread, Eggs, Milk} => {Pencil} 0.06349206 0.6060606 1.6746411
## [108] {Cheese, Eggs, Pencil} => {Bread} 0.06666667 0.6176471 1.2236404
## [109] {Bread, Eggs, Pencil} => {Cheese} 0.06666667 0.6774194 1.3505512
## [110] {Bread, Cheese, Pencil} => {Eggs} 0.06666667 0.5384615 1.2290970
## [111] {Bread, Cheese, Eggs} => {Pencil} 0.06666667 0.5675676 1.5682788
## [112] {Eggs, Pencil} => {Cheese} 0.10793651 0.6538462 1.3035540
## [113] {Cheese, Pencil} => {Eggs} 0.10793651 0.5396825 1.2318841
## [114] {Cheese, Eggs} => {Pencil} 0.10793651 0.3617021 0.9994401
## [115] {Eggs, Pencil} => {Bread} 0.09841270 0.5961538 1.1810595
## [116] {Bread, Pencil} => {Eggs} 0.09841270 0.4920635 1.1231884
## [117] {Bread, Eggs} => {Pencil} 0.09841270 0.5254237 1.4518287
## [118] {Milk, Pencil} => {Eggs} 0.08571429 0.5000000 1.1413043
## [119] {Eggs, Pencil} => {Milk} 0.08571429 0.5192308 1.0351753
## [120] {Eggs, Milk} => {Pencil} 0.08571429 0.3506494 0.9688995
## [121] {Meat, Pencil} => {Eggs} 0.07936508 0.4464286 1.0190217
## [122] {Eggs, Pencil} => {Meat} 0.07936508 0.4807692 1.0096154
## [123] {Eggs, Meat} => {Pencil} 0.07936508 0.2976190 0.8223684
## [124] {Pencil, Wine} => {Eggs} 0.12063492 0.6031746 1.3768116
## [125] {Eggs, Wine} => {Pencil} 0.12063492 0.5000000 1.3815789
## [126] {Eggs, Pencil} => {Wine} 0.12063492 0.7307692 1.6680602
## [127] {Cheese, Meat, Pencil, Wine} => {Bread} 0.05396825 0.7391304 1.4643150
## [128] {Bread, Meat, Pencil, Wine} => {Cheese} 0.05396825 0.7391304 1.4735828
## [129] {Bread, Cheese, Pencil, Wine} => {Meat} 0.05396825 0.7391304 1.5521739
## [130] {Bread, Cheese, Meat, Wine} => {Pencil} 0.05396825 0.6071429 1.6776316
## [131] {Bread, Cheese, Meat, Pencil} => {Wine} 0.05396825 0.6800000 1.5521739
## [132] {Meat, Pencil, Wine} => {Cheese} 0.07301587 0.6388889 1.2737342
## [133] {Cheese, Pencil, Wine} => {Meat} 0.07301587 0.5750000 1.2075000
## [134] {Cheese, Meat, Wine} => {Pencil} 0.07301587 0.4339623 1.1991063
## [135] {Cheese, Meat, Pencil} => {Wine} 0.07301587 0.6969697 1.5909091
## [136] {Meat, Pencil, Wine} => {Bread} 0.07301587 0.6388889 1.2657233
## [137] {Bread, Pencil, Wine} => {Meat} 0.07301587 0.6388889 1.3416667
## [138] {Bread, Meat, Wine} => {Pencil} 0.07301587 0.5476190 1.5131579
## [139] {Bread, Meat, Pencil} => {Wine} 0.07301587 0.6571429 1.5000000
## [140] {Milk, Pencil, Wine} => {Meat} 0.05079365 0.5333333 1.1200000
## [141] {Meat, Pencil, Wine} => {Milk} 0.05079365 0.4444444 0.8860759
## [142] {Meat, Milk, Wine} => {Pencil} 0.05079365 0.4000000 1.1052632
## [143] {Meat, Milk, Pencil} => {Wine} 0.05079365 0.6400000 1.4608696
## [144] {Milk, Pencil, Wine} => {Cheese} 0.06349206 0.6666667 1.3291139
## [145] {Cheese, Pencil, Wine} => {Milk} 0.06349206 0.5000000 0.9968354
## [146] {Cheese, Milk, Wine} => {Pencil} 0.06349206 0.3921569 1.0835913
## [147] {Cheese, Milk, Pencil} => {Wine} 0.06349206 0.6250000 1.4266304
## [148] {Milk, Pencil, Wine} => {Bread} 0.07301587 0.7666667 1.5188679
## [149] {Bread, Pencil, Wine} => {Milk} 0.07301587 0.6388889 1.2737342
## [150] {Bread, Milk, Wine} => {Pencil} 0.07301587 0.5609756 1.5500642
## [151] {Bread, Milk, Pencil} => {Wine} 0.07301587 0.6764706 1.5441176
## [152] {Cheese, Pencil, Wine} => {Bread} 0.07301587 0.5750000 1.1391509
## [153] {Bread, Pencil, Wine} => {Cheese} 0.07301587 0.6388889 1.2737342
## [154] {Bread, Cheese, Wine} => {Pencil} 0.07301587 0.5111111 1.4122807
## [155] {Bread, Cheese, Pencil} => {Wine} 0.07301587 0.5897436 1.3461538
## [156] {Pencil, Wine} => {Cheese} 0.12698413 0.6349206 1.2658228
## [157] {Cheese, Wine} => {Pencil} 0.12698413 0.4705882 1.3003096
## [158] {Cheese, Pencil} => {Wine} 0.12698413 0.6349206 1.4492754
## [159] {Pencil, Wine} => {Bread} 0.11428571 0.5714286 1.1320755
## [160] {Bread, Wine} => {Pencil} 0.11428571 0.4675325 1.2918660
## [161] {Bread, Pencil} => {Wine} 0.11428571 0.5714286 1.3043478
## [162] {Pencil, Wine} => {Milk} 0.09523810 0.4761905 0.9493671
## [163] {Milk, Wine} => {Pencil} 0.09523810 0.4347826 1.2013730
## [164] {Milk, Pencil} => {Wine} 0.09523810 0.5555556 1.2681159
## [165] {Pencil, Wine} => {Meat} 0.11428571 0.5714286 1.2000000
## [166] {Meat, Wine} => {Pencil} 0.11428571 0.4556962 1.2591606
## [167] {Meat, Pencil} => {Wine} 0.11428571 0.6428571 1.4673913
## [168] {Meat, Milk, Pencil} => {Bread} 0.05714286 0.7200000 1.4264151
## [169] {Bread, Milk, Pencil} => {Meat} 0.05714286 0.5294118 1.1117647
## [170] {Bread, Meat, Pencil} => {Milk} 0.05714286 0.5142857 1.0253165
## [171] {Bread, Meat, Milk} => {Pencil} 0.05714286 0.5454545 1.5071770
## [172] {Cheese, Meat, Pencil} => {Bread} 0.07936508 0.7575758 1.5008576
## [173] {Bread, Meat, Pencil} => {Cheese} 0.07936508 0.7142857 1.4240506
## [174] {Bread, Cheese, Pencil} => {Meat} 0.07936508 0.6410256 1.3461538
## [175] {Bread, Cheese, Meat} => {Pencil} 0.07936508 0.5555556 1.5350877
## [176] {Meat, Pencil} => {Cheese} 0.10476190 0.5892857 1.1748418
## [177] {Cheese, Pencil} => {Meat} 0.10476190 0.5238095 1.1000000
## [178] {Cheese, Meat} => {Pencil} 0.10476190 0.3235294 0.8939628
## [179] {Meat, Pencil} => {Bread} 0.11111111 0.6250000 1.2382075
## [180] {Bread, Pencil} => {Meat} 0.11111111 0.5555556 1.1666667
## [181] {Bread, Meat} => {Pencil} 0.11111111 0.5384615 1.4878543
## [182] {Milk, Pencil} => {Meat} 0.07936508 0.4629630 0.9722222
## [183] {Meat, Pencil} => {Milk} 0.07936508 0.4464286 0.8900316
## [184] {Meat, Milk} => {Pencil} 0.07936508 0.3246753 0.8971292
## [185] {Cheese, Milk, Pencil} => {Bread} 0.06349206 0.6250000 1.2382075
## [186] {Bread, Milk, Pencil} => {Cheese} 0.06349206 0.5882353 1.1727476
## [187] {Bread, Cheese, Pencil} => {Milk} 0.06349206 0.5128205 1.0223953
## [188] {Bread, Cheese, Milk} => {Pencil} 0.06349206 0.4878049 1.3478819
## [189] {Milk, Pencil} => {Cheese} 0.10158730 0.5925926 1.1814346
## [190] {Cheese, Pencil} => {Milk} 0.10158730 0.5079365 1.0126582
## [191] {Cheese, Milk} => {Pencil} 0.10158730 0.3333333 0.9210526
## [192] {Milk, Pencil} => {Bread} 0.10793651 0.6296296 1.2473795
## [193] {Bread, Pencil} => {Milk} 0.10793651 0.5396825 1.0759494
## [194] {Bread, Milk} => {Pencil} 0.10793651 0.3863636 1.0675837
## [195] {Cheese, Pencil} => {Bread} 0.12380952 0.6190476 1.2264151
## [196] {Bread, Pencil} => {Cheese} 0.12380952 0.6190476 1.2341772
## [197] {Bread, Cheese} => {Pencil} 0.12380952 0.5200000 1.4368421
## [198] {Pencil} => {Cheese} 0.20000000 0.5526316 1.1017655
## [199] {Cheese} => {Pencil} 0.20000000 0.3987342 1.1017655
## [200] {Pencil} => {Bread} 0.20000000 0.5526316 1.0948361
## [201] {Bread} => {Pencil} 0.20000000 0.3962264 1.0948361
## [202] {Pencil} => {Milk} 0.17142857 0.4736842 0.9443704
## [203] {Milk} => {Pencil} 0.17142857 0.3417722 0.9443704
## [204] {Pencil} => {Meat} 0.17777778 0.4912281 1.0315789
## [205] {Meat} => {Pencil} 0.17777778 0.3733333 1.0315789
## [206] {Wine} => {Pencil} 0.20000000 0.4565217 1.2614416
## [207] {Pencil} => {Wine} 0.20000000 0.5526316 1.2614416
## [208] {Pencil} => {Eggs} 0.16507937 0.4561404 1.0411899
## [209] {Eggs} => {Pencil} 0.16507937 0.3768116 1.0411899
## [210] {Pencil} => {Bagel} 0.15873016 0.4385965 1.0310291
## [211] {Bagel} => {Pencil} 0.15873016 0.3731343 1.0310291
## [212] {Pencil} => {Diaper} 0.17142857 0.4736842 1.1657072
## [213] {Diaper} => {Pencil} 0.17142857 0.4218750 1.1657072
## [214] {Cheese, Diaper, Eggs} => {Bagel} 0.05079365 0.5000000 1.1753731
## [215] {Bagel, Diaper, Eggs} => {Cheese} 0.05079365 0.7272727 1.4499425
## [216] {Bagel, Cheese, Eggs} => {Diaper} 0.05079365 0.5517241 1.3577586
## [217] {Bagel, Cheese, Diaper} => {Eggs} 0.05079365 0.4705882 1.0741688
## [218] {Diaper, Eggs, Meat} => {Bagel} 0.05079365 0.5925926 1.3930348
## [219] {Bagel, Eggs, Meat} => {Diaper} 0.05079365 0.5517241 1.3577586
## [220] {Bagel, Diaper, Meat} => {Eggs} 0.05079365 0.4848485 1.1067194
## [221] {Bagel, Diaper, Eggs} => {Meat} 0.05079365 0.7272727 1.5272727
## [222] {Cheese, Diaper, Wine} => {Bagel} 0.06666667 0.4883721 1.1480389
## [223] {Bagel, Diaper, Wine} => {Cheese} 0.06666667 0.6562500 1.3083465
## [224] {Bagel, Cheese, Wine} => {Diaper} 0.06666667 0.6176471 1.5199908
## [225] {Bagel, Cheese, Diaper} => {Wine} 0.06666667 0.6176471 1.4098465
## [226] {Bread, Diaper, Wine} => {Bagel} 0.06349206 0.4255319 1.0003176
## [227] {Bagel, Diaper, Wine} => {Bread} 0.06349206 0.6250000 1.2382075
## [228] {Bagel, Bread, Wine} => {Diaper} 0.06349206 0.6250000 1.5380859
## [229] {Bagel, Bread, Diaper} => {Wine} 0.06349206 0.5263158 1.2013730
## [230] {Diaper, Meat, Wine} => {Bagel} 0.05396825 0.4358974 1.0246843
## [231] {Bagel, Meat, Wine} => {Diaper} 0.05396825 0.5151515 1.2677557
## [232] {Bagel, Diaper, Wine} => {Meat} 0.05396825 0.5312500 1.1156250
## [233] {Bagel, Diaper, Meat} => {Wine} 0.05396825 0.5151515 1.1758893
## [234] {Cheese, Diaper, Meat} => {Bagel} 0.06984127 0.6111111 1.4365672
## [235] {Bagel, Diaper, Meat} => {Cheese} 0.06984127 0.6666667 1.3291139
## [236] {Bagel, Cheese, Meat} => {Diaper} 0.06984127 0.5789474 1.4247533
## [237] {Bagel, Cheese, Diaper} => {Meat} 0.06984127 0.6470588 1.3588235
## [238] {Bread, Diaper, Meat} => {Bagel} 0.06984127 0.5789474 1.3609584
## [239] {Bagel, Diaper, Meat} => {Bread} 0.06984127 0.6666667 1.3207547
## [240] {Bagel, Bread, Meat} => {Diaper} 0.06984127 0.6111111 1.5039063
## [241] {Bagel, Bread, Diaper} => {Meat} 0.06984127 0.5789474 1.2157895
## [242] {Bread, Diaper, Milk} => {Bagel} 0.05714286 0.5000000 1.1753731
## [243] {Bagel, Diaper, Milk} => {Bread} 0.05714286 0.7200000 1.4264151
## [244] {Bagel, Bread, Milk} => {Diaper} 0.05714286 0.3333333 0.8203125
## [245] {Bagel, Bread, Diaper} => {Milk} 0.05714286 0.4736842 0.9443704
## [246] {Bread, Cheese, Diaper} => {Bagel} 0.06666667 0.4883721 1.1480389
## [247] {Bagel, Cheese, Diaper} => {Bread} 0.06666667 0.6176471 1.2236404
## [248] {Bagel, Bread, Diaper} => {Cheese} 0.06666667 0.5526316 1.1017655
## [249] {Bagel, Bread, Cheese} => {Diaper} 0.06666667 0.6363636 1.5660511
## [250] {Cheese, Diaper} => {Bagel} 0.10793651 0.5396825 1.2686567
## [251] {Bagel, Diaper} => {Cheese} 0.10793651 0.5862069 1.1687036
## [252] {Bagel, Cheese} => {Diaper} 0.10793651 0.5573770 1.3716701
## [253] {Bread, Diaper} => {Bagel} 0.12063492 0.5205479 1.2236761
## [254] {Bagel, Diaper} => {Bread} 0.12063492 0.6551724 1.2979831
## [255] {Bagel, Bread} => {Diaper} 0.12063492 0.4318182 1.0626776
## [256] {Diaper, Milk} => {Bagel} 0.07936508 0.5102041 1.1993603
## [257] {Bagel, Milk} => {Diaper} 0.07936508 0.3521127 0.8665273
## [258] {Bagel, Diaper} => {Milk} 0.07936508 0.4310345 0.8593409
## [259] {Diaper, Meat} => {Bagel} 0.10476190 0.5409836 1.2717152
## [260] {Bagel, Meat} => {Diaper} 0.10476190 0.5500000 1.3535156
## [261] {Bagel, Diaper} => {Meat} 0.10476190 0.5689655 1.1948276
## [262] {Diaper, Wine} => {Bagel} 0.10158730 0.4324324 1.0165389
## [263] {Bagel, Wine} => {Diaper} 0.10158730 0.5925926 1.4583333
## [264] {Bagel, Diaper} => {Wine} 0.10158730 0.5517241 1.2593703
## [265] {Diaper, Eggs} => {Bagel} 0.06984127 0.4313725 1.0140474
## [266] {Bagel, Eggs} => {Diaper} 0.06984127 0.4583333 1.1279297
## [267] {Bagel, Diaper} => {Eggs} 0.06984127 0.3793103 0.8658171
## [268] {Diaper, Eggs, Wine} => {Cheese} 0.06984127 0.6285714 1.2531646
## [269] {Cheese, Eggs, Wine} => {Diaper} 0.06984127 0.4230769 1.0411659
## [270] {Cheese, Diaper, Wine} => {Eggs} 0.06984127 0.5116279 1.1678463
## [271] {Cheese, Diaper, Eggs} => {Wine} 0.06984127 0.6875000 1.5692935
## [272] {Diaper, Eggs, Wine} => {Bread} 0.06349206 0.5714286 1.1320755
## [273] {Bread, Eggs, Wine} => {Diaper} 0.06349206 0.5263158 1.2952303
## [274] {Bread, Diaper, Wine} => {Eggs} 0.06349206 0.4255319 0.9713228
## [275] {Bread, Diaper, Eggs} => {Wine} 0.06349206 0.7142857 1.6304348
## [276] {Eggs, Meat, Wine} => {Diaper} 0.05714286 0.3829787 0.9424867
## [277] {Diaper, Meat, Wine} => {Eggs} 0.05714286 0.4615385 1.0535117
## [278] {Diaper, Eggs, Wine} => {Meat} 0.05714286 0.5142857 1.0800000
## [279] {Diaper, Eggs, Meat} => {Wine} 0.05714286 0.6666667 1.5217391
## [280] {Diaper, Eggs, Meat} => {Cheese} 0.06031746 0.7037037 1.4029536
## [281] {Cheese, Eggs, Meat} => {Diaper} 0.06031746 0.2794118 0.6876149
## [282] {Cheese, Diaper, Meat} => {Eggs} 0.06031746 0.5277778 1.2047101
## [283] {Cheese, Diaper, Eggs} => {Meat} 0.06031746 0.5937500 1.2468750
## [284] {Diaper, Eggs, Milk} => {Bread} 0.05079365 0.6956522 1.3781788
## [285] {Bread, Eggs, Milk} => {Diaper} 0.05079365 0.4848485 1.1931818
## [286] {Bread, Diaper, Milk} => {Eggs} 0.05079365 0.4444444 1.0144928
## [287] {Bread, Diaper, Eggs} => {Milk} 0.05079365 0.5714286 1.1392405
## [288] {Cheese, Diaper, Eggs} => {Bread} 0.05714286 0.5625000 1.1143868
## [289] {Bread, Diaper, Eggs} => {Cheese} 0.05714286 0.6428571 1.2816456
## [290] {Bread, Cheese, Eggs} => {Diaper} 0.05714286 0.4864865 1.1972128
## [291] {Bread, Cheese, Diaper} => {Eggs} 0.05714286 0.4186047 0.9555106
## [292] {Diaper, Eggs} => {Cheese} 0.10158730 0.6274510 1.2509308
## [293] {Cheese, Eggs} => {Diaper} 0.10158730 0.3404255 0.8377660
## [294] {Cheese, Diaper} => {Eggs} 0.10158730 0.5079365 1.1594203
## [295] {Diaper, Eggs} => {Bread} 0.08888889 0.5490196 1.0876804
## [296] {Bread, Eggs} => {Diaper} 0.08888889 0.4745763 1.1679025
## [297] {Bread, Diaper} => {Eggs} 0.08888889 0.3835616 0.8755211
## [298] {Eggs, Milk} => {Diaper} 0.07301587 0.2987013 0.7350852
## [299] {Diaper, Milk} => {Eggs} 0.07301587 0.4693878 1.0714286
## [300] {Diaper, Eggs} => {Milk} 0.07301587 0.4509804 0.8991065
## [301] {Eggs, Meat} => {Diaper} 0.08571429 0.3214286 0.7910156
## [302] {Diaper, Meat} => {Eggs} 0.08571429 0.4426230 1.0103350
## [303] {Diaper, Eggs} => {Meat} 0.08571429 0.5294118 1.1117647
## [304] {Eggs, Wine} => {Diaper} 0.11111111 0.4605263 1.1333265
## [305] {Diaper, Wine} => {Eggs} 0.11111111 0.4729730 1.0796122
## [306] {Diaper, Eggs} => {Wine} 0.11111111 0.6862745 1.5664962
## [307] {Diaper, Meat, Wine} => {Cheese} 0.07301587 0.5897436 1.1757546
## [308] {Cheese, Meat, Wine} => {Diaper} 0.07301587 0.4339623 1.0679540
## [309] {Cheese, Diaper, Wine} => {Meat} 0.07301587 0.5348837 1.1232558
## [310] {Cheese, Diaper, Meat} => {Wine} 0.07301587 0.6388889 1.4583333
## [311] {Diaper, Meat, Wine} => {Bread} 0.07619048 0.6153846 1.2191582
## [312] {Bread, Meat, Wine} => {Diaper} 0.07619048 0.5714286 1.4062500
## [313] {Bread, Diaper, Wine} => {Meat} 0.07619048 0.5106383 1.0723404
## [314] {Bread, Diaper, Meat} => {Wine} 0.07619048 0.6315789 1.4416476
## [315] {Diaper, Milk, Wine} => {Cheese} 0.06666667 0.7241379 1.4436927
## [316] {Cheese, Milk, Wine} => {Diaper} 0.06666667 0.4117647 1.0133272
## [317] {Cheese, Diaper, Wine} => {Milk} 0.06666667 0.4883721 0.9736532
## [318] {Cheese, Diaper, Milk} => {Wine} 0.06666667 0.7000000 1.5978261
## [319] {Diaper, Milk, Wine} => {Bread} 0.06666667 0.7241379 1.4346129
## [320] {Bread, Milk, Wine} => {Diaper} 0.06666667 0.5121951 1.2604802
## [321] {Bread, Diaper, Wine} => {Milk} 0.06666667 0.4468085 0.8907891
## [322] {Bread, Diaper, Milk} => {Wine} 0.06666667 0.5833333 1.3315217
## [323] {Cheese, Diaper, Wine} => {Bread} 0.08571429 0.6279070 1.2439667
## [324] {Bread, Diaper, Wine} => {Cheese} 0.08571429 0.5744681 1.1453003
## [325] {Bread, Cheese, Wine} => {Diaper} 0.08571429 0.6000000 1.4765625
## [326] {Bread, Cheese, Diaper} => {Wine} 0.08571429 0.6279070 1.4332659
## [327] {Diaper, Wine} => {Cheese} 0.13650794 0.5810811 1.1584844
## [328] {Cheese, Wine} => {Diaper} 0.13650794 0.5058824 1.2449449
## [329] {Cheese, Diaper} => {Wine} 0.13650794 0.6825397 1.5579710
## [330] {Diaper, Wine} => {Bread} 0.14920635 0.6351351 1.2582866
## [331] {Bread, Wine} => {Diaper} 0.14920635 0.6103896 1.5021307
## [332] {Bread, Diaper} => {Wine} 0.14920635 0.6438356 1.4696248
## [333] {Milk, Wine} => {Diaper} 0.09206349 0.4202899 1.0343071
## [334] {Diaper, Wine} => {Milk} 0.09206349 0.3918919 0.7813035
## [335] {Diaper, Milk} => {Wine} 0.09206349 0.5918367 1.3509317
## [336] {Meat, Wine} => {Diaper} 0.12380952 0.4936709 1.2148932
## [337] {Diaper, Wine} => {Meat} 0.12380952 0.5270270 1.1067568
## [338] {Diaper, Meat} => {Wine} 0.12380952 0.6393443 1.4593728
## [339] {Diaper, Meat, Milk} => {Bread} 0.05396825 0.8500000 1.6839623
## [340] {Bread, Meat, Milk} => {Diaper} 0.05396825 0.5151515 1.2677557
## [341] {Bread, Diaper, Milk} => {Meat} 0.05396825 0.4722222 0.9916667
## [342] {Bread, Diaper, Meat} => {Milk} 0.05396825 0.4473684 0.8919054
## [343] {Cheese, Diaper, Meat} => {Bread} 0.07936508 0.6944444 1.3757862
## [344] {Bread, Diaper, Meat} => {Cheese} 0.07936508 0.6578947 1.3116256
## [345] {Bread, Cheese, Meat} => {Diaper} 0.07936508 0.5555556 1.3671875
## [346] {Bread, Cheese, Diaper} => {Meat} 0.07936508 0.5813953 1.2209302
## [347] {Diaper, Meat} => {Cheese} 0.11428571 0.5901639 1.1765927
## [348] {Cheese, Meat} => {Diaper} 0.11428571 0.3529412 0.8685662
## [349] {Cheese, Diaper} => {Meat} 0.11428571 0.5714286 1.2000000
## [350] {Diaper, Meat} => {Bread} 0.12063492 0.6229508 1.2341479
## [351] {Bread, Meat} => {Diaper} 0.12063492 0.5846154 1.4387019
## [352] {Bread, Diaper} => {Meat} 0.12063492 0.5205479 1.0931507
## [353] {Meat, Milk} => {Diaper} 0.06349206 0.2597403 0.6392045
## [354] {Diaper, Milk} => {Meat} 0.06349206 0.4081633 0.8571429
## [355] {Diaper, Meat} => {Milk} 0.06349206 0.3278689 0.6536626
## [356] {Cheese, Diaper, Milk} => {Bread} 0.06666667 0.7000000 1.3867925
## [357] {Bread, Diaper, Milk} => {Cheese} 0.06666667 0.5833333 1.1629747
## [358] {Bread, Cheese, Milk} => {Diaper} 0.06666667 0.5121951 1.2604802
## [359] {Bread, Cheese, Diaper} => {Milk} 0.06666667 0.4883721 0.9736532
## [360] {Diaper, Milk} => {Cheese} 0.09523810 0.6122449 1.2206148
## [361] {Cheese, Milk} => {Diaper} 0.09523810 0.3125000 0.7690430
## [362] {Cheese, Diaper} => {Milk} 0.09523810 0.4761905 0.9493671
## [363] {Diaper, Milk} => {Bread} 0.11428571 0.7346939 1.4555256
## [364] {Bread, Milk} => {Diaper} 0.11428571 0.4090909 1.0067472
## [365] {Bread, Diaper} => {Milk} 0.11428571 0.4931507 0.9831802
## [366] {Cheese, Diaper} => {Bread} 0.13650794 0.6825397 1.3522013
## [367] {Bread, Diaper} => {Cheese} 0.13650794 0.5890411 1.1743541
## [368] {Bread, Cheese} => {Diaper} 0.13650794 0.5733333 1.4109375
## [369] {Diaper} => {Cheese} 0.20000000 0.4921875 0.9812599
## [370] {Cheese} => {Diaper} 0.20000000 0.3987342 0.9812599
## [371] {Diaper} => {Bread} 0.23174603 0.5703125 1.1298644
## [372] {Bread} => {Diaper} 0.23174603 0.4591195 1.1298644
## [373] {Milk} => {Diaper} 0.15555556 0.3101266 0.7632021
## [374] {Diaper} => {Milk} 0.15555556 0.3828125 0.7632021
## [375] {Meat} => {Diaper} 0.19365079 0.4066667 1.0007812
## [376] {Diaper} => {Meat} 0.19365079 0.4765625 1.0007812
## [377] {Wine} => {Diaper} 0.23492063 0.5362319 1.3196332
## [378] {Diaper} => {Wine} 0.23492063 0.5781250 1.3196332
## [379] {Eggs} => {Diaper} 0.16190476 0.3695652 0.9094769
## [380] {Diaper} => {Eggs} 0.16190476 0.3984375 0.9094769
## [381] {Diaper} => {Bagel} 0.18412698 0.4531250 1.0651819
## [382] {Bagel} => {Diaper} 0.18412698 0.4328358 1.0651819
## [383] {Cheese, Eggs, Wine} => {Bagel} 0.05714286 0.3461538 0.8137199
## [384] {Bagel, Eggs, Wine} => {Cheese} 0.05714286 0.6206897 1.2374509
## [385] {Bagel, Cheese, Wine} => {Eggs} 0.05714286 0.5294118 1.2084399
## [386] {Bagel, Cheese, Eggs} => {Wine} 0.05714286 0.6206897 1.4167916
## [387] {Bread, Eggs, Wine} => {Bagel} 0.05079365 0.4210526 0.9897879
## [388] {Bagel, Eggs, Wine} => {Bread} 0.05079365 0.5517241 1.0930384
## [389] {Bagel, Bread, Wine} => {Eggs} 0.05079365 0.5000000 1.1413043
## [390] {Bagel, Bread, Eggs} => {Wine} 0.05079365 0.5925926 1.3526570
## [391] {Eggs, Meat, Wine} => {Bagel} 0.05714286 0.3829787 0.9002858
## [392] {Bagel, Meat, Wine} => {Eggs} 0.05714286 0.5454545 1.2450593
## [393] {Bagel, Eggs, Wine} => {Meat} 0.05714286 0.6206897 1.3034483
## [394] {Bagel, Eggs, Meat} => {Wine} 0.05714286 0.6206897 1.4167916
## [395] {Cheese, Eggs, Meat} => {Bagel} 0.06349206 0.2941176 0.6913960
## [396] {Bagel, Eggs, Meat} => {Cheese} 0.06349206 0.6896552 1.3749454
## [397] {Bagel, Cheese, Meat} => {Eggs} 0.06349206 0.5263158 1.2013730
## [398] {Bagel, Cheese, Eggs} => {Meat} 0.06349206 0.6896552 1.4482759
## [399] {Cheese, Eggs} => {Bagel} 0.09206349 0.3085106 0.7252302
## [400] {Bagel, Eggs} => {Cheese} 0.09206349 0.6041667 1.2045095
## [401] {Bagel, Cheese} => {Eggs} 0.09206349 0.4754098 1.0851746
## [402] {Bread, Eggs} => {Bagel} 0.08571429 0.4576271 1.0757652
## [403] {Bagel, Eggs} => {Bread} 0.08571429 0.5625000 1.1143868
## [404] {Bagel, Bread} => {Eggs} 0.08571429 0.3068182 0.7003458
## [405] {Eggs, Milk} => {Bagel} 0.06349206 0.2597403 0.6105834
## [406] {Bagel, Milk} => {Eggs} 0.06349206 0.2816901 0.6429884
## [407] {Bagel, Eggs} => {Milk} 0.06349206 0.4166667 0.8306962
## [408] {Eggs, Meat} => {Bagel} 0.09206349 0.3452381 0.8115672
## [409] {Bagel, Meat} => {Eggs} 0.09206349 0.4833333 1.1032609
## [410] {Bagel, Eggs} => {Meat} 0.09206349 0.6041667 1.2687500
## [411] {Eggs, Wine} => {Bagel} 0.09206349 0.3815789 0.8969953
## [412] {Bagel, Wine} => {Eggs} 0.09206349 0.5370370 1.2258454
## [413] {Bagel, Eggs} => {Wine} 0.09206349 0.6041667 1.3790761
## [414] {Cheese, Meat, Wine} => {Bagel} 0.06349206 0.3773585 0.8870741
## [415] {Bagel, Meat, Wine} => {Cheese} 0.06349206 0.6060606 1.2082854
## [416] {Bagel, Cheese, Wine} => {Meat} 0.06349206 0.5882353 1.2352941
## [417] {Bagel, Cheese, Meat} => {Wine} 0.06349206 0.5263158 1.2013730
## [418] {Bread, Meat, Wine} => {Bagel} 0.06031746 0.4523810 1.0634328
## [419] {Bagel, Meat, Wine} => {Bread} 0.06031746 0.5757576 1.1406518
## [420] {Bagel, Bread, Wine} => {Meat} 0.06031746 0.5937500 1.2468750
## [421] {Bagel, Bread, Meat} => {Wine} 0.06031746 0.5277778 1.2047101
## [422] {Cheese, Milk, Wine} => {Bagel} 0.05714286 0.3529412 0.8296752
## [423] {Bagel, Milk, Wine} => {Cheese} 0.05714286 0.6428571 1.2816456
## [424] {Bagel, Cheese, Wine} => {Milk} 0.05714286 0.5294118 1.0554728
## [425] {Bagel, Cheese, Milk} => {Wine} 0.05714286 0.6428571 1.4673913
## [426] {Bread, Milk, Wine} => {Bagel} 0.05714286 0.4390244 1.0320349
## [427] {Bagel, Milk, Wine} => {Bread} 0.05714286 0.6428571 1.2735849
## [428] {Bagel, Bread, Wine} => {Milk} 0.05714286 0.5625000 1.1214399
## [429] {Bagel, Bread, Milk} => {Wine} 0.05714286 0.3333333 0.7608696
## [430] {Bread, Cheese, Wine} => {Bagel} 0.05714286 0.4000000 0.9402985
## [431] {Bagel, Cheese, Wine} => {Bread} 0.05714286 0.5294118 1.0488346
## [432] {Bagel, Bread, Wine} => {Cheese} 0.05714286 0.5625000 1.1214399
## [433] {Bagel, Bread, Cheese} => {Wine} 0.05714286 0.5454545 1.2450593
## [434] {Cheese, Wine} => {Bagel} 0.10793651 0.4000000 0.9402985
## [435] {Bagel, Wine} => {Cheese} 0.10793651 0.6296296 1.2552743
## [436] {Bagel, Cheese} => {Wine} 0.10793651 0.5573770 1.2722737
## [437] {Bread, Wine} => {Bagel} 0.10158730 0.4155844 0.9769335
## [438] {Bagel, Wine} => {Bread} 0.10158730 0.5925926 1.1740042
## [439] {Bagel, Bread} => {Wine} 0.10158730 0.3636364 0.8300395
## [440] {Milk, Wine} => {Bagel} 0.08888889 0.4057971 0.9539260
## [441] {Bagel, Wine} => {Milk} 0.08888889 0.5185185 1.0337553
## [442] {Bagel, Milk} => {Wine} 0.08888889 0.3943662 0.9001837
## [443] {Meat, Wine} => {Bagel} 0.10476190 0.4177215 0.9819573
## [444] {Bagel, Wine} => {Meat} 0.10476190 0.6111111 1.2833333
## [445] {Bagel, Meat} => {Wine} 0.10476190 0.5500000 1.2554348
## [446] {Cheese, Meat, Milk} => {Bagel} 0.05079365 0.2500000 0.5876866
## [447] {Bagel, Meat, Milk} => {Cheese} 0.05079365 0.6666667 1.3291139
## [448] {Bagel, Cheese, Milk} => {Meat} 0.05079365 0.5714286 1.2000000
## [449] {Bagel, Cheese, Meat} => {Milk} 0.05079365 0.4210526 0.8394404
## [450] {Bread, Cheese, Meat} => {Bagel} 0.06666667 0.4666667 1.0970149
## [451] {Bagel, Cheese, Meat} => {Bread} 0.06666667 0.5526316 1.0948361
## [452] {Bagel, Bread, Meat} => {Cheese} 0.06666667 0.5833333 1.1629747
## [453] {Bagel, Bread, Cheese} => {Meat} 0.06666667 0.6363636 1.3363636
## [454] {Cheese, Meat} => {Bagel} 0.12063492 0.3725490 0.8757682
## [455] {Bagel, Meat} => {Cheese} 0.12063492 0.6333333 1.2626582
## [456] {Bagel, Cheese} => {Meat} 0.12063492 0.6229508 1.3081967
## [457] {Bread, Meat} => {Bagel} 0.11428571 0.5538462 1.3019518
## [458] {Bagel, Meat} => {Bread} 0.11428571 0.6000000 1.1886792
## [459] {Bagel, Bread} => {Meat} 0.11428571 0.4090909 0.8590909
## [460] {Meat, Milk} => {Bagel} 0.07619048 0.3116883 0.7327001
## [461] {Bagel, Milk} => {Meat} 0.07619048 0.3380282 0.7098592
## [462] {Bagel, Meat} => {Milk} 0.07619048 0.4000000 0.7974684
## [463] {Cheese, Milk} => {Bagel} 0.08888889 0.2916667 0.6856343
## [464] {Bagel, Milk} => {Cheese} 0.08888889 0.3943662 0.7862364
## [465] {Bagel, Cheese} => {Milk} 0.08888889 0.4590164 0.9151276
## [466] {Bread, Milk} => {Bagel} 0.17142857 0.6136364 1.4425034
## [467] {Bagel, Milk} => {Bread} 0.17142857 0.7605634 1.5067765
## [468] {Bagel, Bread} => {Milk} 0.17142857 0.6136364 1.2233890
## [469] {Bread, Cheese} => {Bagel} 0.10476190 0.4400000 1.0343284
## [470] {Bagel, Cheese} => {Bread} 0.10476190 0.5409836 1.0717600
## [471] {Bagel, Bread} => {Cheese} 0.10476190 0.3750000 0.7476266
## [472] {Cheese} => {Bagel} 0.19365079 0.3860759 0.9075666
## [473] {Bagel} => {Cheese} 0.19365079 0.4552239 0.9075666
## [474] {Bread} => {Bagel} 0.27936508 0.5534591 1.3010420
## [475] {Bagel} => {Bread} 0.27936508 0.6567164 1.3010420
## [476] {Milk} => {Bagel} 0.22539683 0.4493671 1.0563480
## [477] {Bagel} => {Milk} 0.22539683 0.5298507 1.0563480
## [478] {Meat} => {Bagel} 0.19047619 0.4000000 0.9402985
## [479] {Bagel} => {Meat} 0.19047619 0.4477612 0.9402985
## [480] {Wine} => {Bagel} 0.17142857 0.3913043 0.9198572
## [481] {Bagel} => {Wine} 0.17142857 0.4029851 0.9198572
## [482] {Eggs} => {Bagel} 0.15238095 0.3478261 0.8176509
## [483] {Bagel} => {Eggs} 0.15238095 0.3582090 0.8176509
## [484] {Eggs, Meat, Milk, Wine} => {Cheese} 0.07301587 0.7931034 1.5811873
## [485] {Cheese, Meat, Milk, Wine} => {Eggs} 0.07301587 0.7187500 1.6406250
## [486] {Cheese, Eggs, Milk, Wine} => {Meat} 0.07301587 0.6969697 1.4636364
## [487] {Cheese, Eggs, Meat, Wine} => {Milk} 0.07301587 0.6571429 1.3101266
## [488] {Cheese, Eggs, Meat, Milk} => {Wine} 0.07301587 0.4791667 1.0937500
## [489] {Eggs, Meat, Wine} => {Cheese} 0.11111111 0.7446809 1.4846485
## [490] {Cheese, Meat, Wine} => {Eggs} 0.11111111 0.6603774 1.5073831
## [491] {Cheese, Eggs, Wine} => {Meat} 0.11111111 0.6730769 1.4134615
## [492] {Cheese, Eggs, Meat} => {Wine} 0.11111111 0.5147059 1.1748721
## [493] {Eggs, Meat, Wine} => {Bread} 0.06349206 0.4255319 0.8430349
## [494] {Bread, Meat, Wine} => {Eggs} 0.06349206 0.4761905 1.0869565
## [495] {Bread, Eggs, Wine} => {Meat} 0.06349206 0.5263158 1.1052632
## [496] {Bread, Eggs, Meat} => {Wine} 0.06349206 0.6896552 1.5742129
## [497] {Meat, Milk, Wine} => {Eggs} 0.09206349 0.7250000 1.6548913
## [498] {Eggs, Milk, Wine} => {Meat} 0.09206349 0.6744186 1.4162791
## [499] {Eggs, Meat, Wine} => {Milk} 0.09206349 0.6170213 1.2301374
## [500] {Eggs, Meat, Milk} => {Wine} 0.09206349 0.5178571 1.1820652
## [501] {Cheese, Eggs, Milk, Wine} => {Bread} 0.05079365 0.4848485 0.9605489
## [502] {Bread, Eggs, Milk, Wine} => {Cheese} 0.05079365 0.6666667 1.3291139
## [503] {Bread, Cheese, Milk, Wine} => {Eggs} 0.05079365 0.5925926 1.3526570
## [504] {Bread, Cheese, Eggs, Wine} => {Milk} 0.05079365 0.6956522 1.3869015
## [505] {Bread, Cheese, Eggs, Milk} => {Wine} 0.05079365 0.6956522 1.5879017
## [506] {Eggs, Milk, Wine} => {Cheese} 0.10476190 0.7674419 1.5300265
## [507] {Cheese, Milk, Wine} => {Eggs} 0.10476190 0.6470588 1.4769821
## [508] {Cheese, Eggs, Wine} => {Milk} 0.10476190 0.6346154 1.2652142
## [509] {Cheese, Eggs, Milk} => {Wine} 0.10476190 0.5322581 1.2149369
## [510] {Eggs, Milk, Wine} => {Bread} 0.07619048 0.5581395 1.1057481
## [511] {Bread, Milk, Wine} => {Eggs} 0.07619048 0.5853659 1.3361612
## [512] {Bread, Eggs, Wine} => {Milk} 0.07619048 0.6315789 1.2591606
## [513] {Bread, Eggs, Milk} => {Wine} 0.07619048 0.7272727 1.6600791
## [514] {Cheese, Eggs, Wine} => {Bread} 0.07301587 0.4423077 0.8762700
## [515] {Bread, Eggs, Wine} => {Cheese} 0.07301587 0.6052632 1.2066955
## [516] {Bread, Cheese, Wine} => {Eggs} 0.07301587 0.5111111 1.1666667
## [517] {Bread, Cheese, Eggs} => {Wine} 0.07301587 0.6216216 1.4189189
## [518] {Eggs, Wine} => {Cheese} 0.16507937 0.6842105 1.3640906
## [519] {Cheese, Wine} => {Eggs} 0.16507937 0.6117647 1.3964194
## [520] {Cheese, Eggs} => {Wine} 0.16507937 0.5531915 1.2627197
## [521] {Eggs, Wine} => {Bread} 0.12063492 0.5000000 0.9905660
## [522] {Bread, Wine} => {Eggs} 0.12063492 0.4935065 1.1264822
## [523] {Bread, Eggs} => {Wine} 0.12063492 0.6440678 1.4701548
## [524] {Milk, Wine} => {Eggs} 0.13650794 0.6231884 1.4224953
## [525] {Eggs, Wine} => {Milk} 0.13650794 0.5657895 1.1279980
## [526] {Eggs, Milk} => {Wine} 0.13650794 0.5584416 1.2747036
## [527] {Meat, Wine} => {Eggs} 0.14920635 0.5949367 1.3580077
## [528] {Eggs, Wine} => {Meat} 0.14920635 0.6184211 1.2986842
## [529] {Eggs, Meat} => {Wine} 0.14920635 0.5595238 1.2771739
## [530] {Eggs, Meat, Milk} => {Cheese} 0.15238095 0.8571429 1.7088608
## [531] {Cheese, Meat, Milk} => {Eggs} 0.15238095 0.7500000 1.7119565
## [532] {Cheese, Eggs, Milk} => {Meat} 0.15238095 0.7741935 1.6258065
## [533] {Cheese, Eggs, Meat} => {Milk} 0.15238095 0.7058824 1.4072971
## [534] {Eggs, Meat, Milk} => {Bread} 0.06031746 0.3392857 0.6721698
## [535] {Bread, Meat, Milk} => {Eggs} 0.06031746 0.5757576 1.3142292
## [536] {Bread, Eggs, Milk} => {Meat} 0.06031746 0.5757576 1.2090909
## [537] {Bread, Eggs, Meat} => {Milk} 0.06031746 0.6551724 1.3061982
## [538] {Cheese, Eggs, Meat} => {Bread} 0.06349206 0.2941176 0.5826859
## [539] {Bread, Eggs, Meat} => {Cheese} 0.06349206 0.6896552 1.3749454
## [540] {Bread, Cheese, Meat} => {Eggs} 0.06349206 0.4444444 1.0144928
## [541] {Bread, Cheese, Eggs} => {Meat} 0.06349206 0.5405405 1.1351351
## [542] {Eggs, Meat} => {Cheese} 0.21587302 0.8095238 1.6139241
## [543] {Cheese, Meat} => {Eggs} 0.21587302 0.6666667 1.5217391
## [544] {Cheese, Eggs} => {Meat} 0.21587302 0.7234043 1.5191489
## [545] {Eggs, Meat} => {Bread} 0.09206349 0.3452381 0.6839623
## [546] {Bread, Meat} => {Eggs} 0.09206349 0.4461538 1.0183946
## [547] {Bread, Eggs} => {Meat} 0.09206349 0.4915254 1.0322034
## [548] {Meat, Milk} => {Eggs} 0.17777778 0.7272727 1.6600791
## [549] {Eggs, Milk} => {Meat} 0.17777778 0.7272727 1.5272727
## [550] {Eggs, Meat} => {Milk} 0.17777778 0.6666667 1.3291139
## [551] {Cheese, Eggs, Milk} => {Bread} 0.07301587 0.3709677 0.7349361
## [552] {Bread, Eggs, Milk} => {Cheese} 0.07301587 0.6969697 1.3895282
## [553] {Bread, Cheese, Milk} => {Eggs} 0.07301587 0.5609756 1.2804878
## [554] {Bread, Cheese, Eggs} => {Milk} 0.07301587 0.6216216 1.2393089
## [555] {Eggs, Milk} => {Cheese} 0.19682540 0.8051948 1.6052934
## [556] {Cheese, Milk} => {Eggs} 0.19682540 0.6458333 1.4741848
## [557] {Cheese, Eggs} => {Milk} 0.19682540 0.6595745 1.3149744
## [558] {Eggs, Milk} => {Bread} 0.10476190 0.4285714 0.8490566
## [559] {Bread, Milk} => {Eggs} 0.10476190 0.3750000 0.8559783
## [560] {Bread, Eggs} => {Milk} 0.10476190 0.5593220 1.1151041
## [561] {Cheese, Eggs} => {Bread} 0.11746032 0.3936170 0.7798073
## [562] {Bread, Eggs} => {Cheese} 0.11746032 0.6271186 1.2502682
## [563] {Bread, Cheese} => {Eggs} 0.11746032 0.4933333 1.1260870
## [564] {Eggs} => {Cheese} 0.29841270 0.6811594 1.3580077
## [565] {Cheese} => {Eggs} 0.29841270 0.5949367 1.3580077
## [566] {Eggs} => {Bread} 0.18730159 0.4275362 0.8470057
## [567] {Bread} => {Eggs} 0.18730159 0.3710692 0.8470057
## [568] {Milk} => {Eggs} 0.24444444 0.4873418 1.1124106
## [569] {Eggs} => {Milk} 0.24444444 0.5579710 1.1124106
## [570] {Meat} => {Eggs} 0.26666667 0.5600000 1.2782609
## [571] {Eggs} => {Meat} 0.26666667 0.6086957 1.2782609
## [572] {Wine} => {Eggs} 0.24126984 0.5507246 1.2570888
## [573] {Eggs} => {Wine} 0.24126984 0.5507246 1.2570888
## [574] {Cheese, Meat, Milk, Wine} => {Bread} 0.05396825 0.5312500 1.0524764
## [575] {Bread, Meat, Milk, Wine} => {Cheese} 0.05396825 0.7083333 1.4121835
## [576] {Bread, Cheese, Milk, Wine} => {Meat} 0.05396825 0.6296296 1.3222222
## [577] {Bread, Cheese, Meat, Wine} => {Milk} 0.05396825 0.6071429 1.2104430
## [578] {Bread, Cheese, Meat, Milk} => {Wine} 0.05396825 0.7083333 1.6168478
## [579] {Meat, Milk, Wine} => {Cheese} 0.10158730 0.8000000 1.5949367
## [580] {Cheese, Milk, Wine} => {Meat} 0.10158730 0.6274510 1.3176471
## [581] {Cheese, Meat, Wine} => {Milk} 0.10158730 0.6037736 1.2037258
## [582] {Cheese, Meat, Milk} => {Wine} 0.10158730 0.5000000 1.1413043
## [583] {Meat, Milk, Wine} => {Bread} 0.07619048 0.6000000 1.1886792
## [584] {Bread, Milk, Wine} => {Meat} 0.07619048 0.5853659 1.2292683
## [585] {Bread, Meat, Wine} => {Milk} 0.07619048 0.5714286 1.1392405
## [586] {Bread, Meat, Milk} => {Wine} 0.07619048 0.7272727 1.6600791
## [587] {Cheese, Meat, Wine} => {Bread} 0.08888889 0.5283019 1.0466358
## [588] {Bread, Meat, Wine} => {Cheese} 0.08888889 0.6666667 1.3291139
## [589] {Bread, Cheese, Wine} => {Meat} 0.08888889 0.6222222 1.3066667
## [590] {Bread, Cheese, Meat} => {Wine} 0.08888889 0.6222222 1.4202899
## [591] {Meat, Wine} => {Cheese} 0.16825397 0.6708861 1.3375260
## [592] {Cheese, Wine} => {Meat} 0.16825397 0.6235294 1.3094118
## [593] {Cheese, Meat} => {Wine} 0.16825397 0.5196078 1.1860614
## [594] {Meat, Wine} => {Bread} 0.13333333 0.5316456 1.0532601
## [595] {Bread, Wine} => {Meat} 0.13333333 0.5454545 1.1454545
## [596] {Bread, Meat} => {Wine} 0.13333333 0.6461538 1.4749164
## [597] {Milk, Wine} => {Meat} 0.12698413 0.5797101 1.2173913
## [598] {Meat, Wine} => {Milk} 0.12698413 0.5063291 1.0094536
## [599] {Meat, Milk} => {Wine} 0.12698413 0.5194805 1.1857708
## [600] {Cheese, Milk, Wine} => {Bread} 0.08571429 0.5294118 1.0488346
## [601] {Bread, Milk, Wine} => {Cheese} 0.08571429 0.6585366 1.3129052
## [602] {Bread, Cheese, Wine} => {Milk} 0.08571429 0.6000000 1.1962025
## [603] {Bread, Cheese, Milk} => {Wine} 0.08571429 0.6585366 1.5031813
## [604] {Milk, Wine} => {Cheese} 0.16190476 0.7391304 1.4735828
## [605] {Cheese, Wine} => {Milk} 0.16190476 0.6000000 1.1962025
## [606] {Cheese, Milk} => {Wine} 0.16190476 0.5312500 1.2126359
## [607] {Milk, Wine} => {Bread} 0.13015873 0.5942029 1.1771944
## [608] {Bread, Wine} => {Milk} 0.13015873 0.5324675 1.0615650
## [609] {Bread, Milk} => {Wine} 0.13015873 0.4659091 1.0634881
## [610] {Cheese, Wine} => {Bread} 0.14285714 0.5294118 1.0488346
## [611] {Bread, Wine} => {Cheese} 0.14285714 0.5844156 1.1651323
## [612] {Bread, Cheese} => {Wine} 0.14285714 0.6000000 1.3695652
## [613] {Wine} => {Cheese} 0.26984127 0.6159420 1.2279857
## [614] {Cheese} => {Wine} 0.26984127 0.5379747 1.2279857
## [615] {Wine} => {Bread} 0.24444444 0.5579710 1.1054143
## [616] {Bread} => {Wine} 0.24444444 0.4842767 1.1054143
## [617] {Wine} => {Milk} 0.21904762 0.5000000 0.9968354
## [618] {Milk} => {Wine} 0.21904762 0.4367089 0.9968354
## [619] {Wine} => {Meat} 0.25079365 0.5724638 1.2021739
## [620] {Meat} => {Wine} 0.25079365 0.5266667 1.2021739
## [621] {Cheese, Meat, Milk} => {Bread} 0.07619048 0.3750000 0.7429245
## [622] {Bread, Meat, Milk} => {Cheese} 0.07619048 0.7272727 1.4499425
## [623] {Bread, Cheese, Milk} => {Meat} 0.07619048 0.5853659 1.2292683
## [624] {Bread, Cheese, Meat} => {Milk} 0.07619048 0.5333333 1.0632911
## [625] {Meat, Milk} => {Cheese} 0.20317460 0.8311688 1.6570771
## [626] {Cheese, Milk} => {Meat} 0.20317460 0.6666667 1.4000000
## [627] {Cheese, Meat} => {Milk} 0.20317460 0.6274510 1.2509308
## [628] {Meat, Milk} => {Bread} 0.10476190 0.4285714 0.8490566
## [629] {Bread, Milk} => {Meat} 0.10476190 0.3750000 0.7875000
## [630] {Bread, Meat} => {Milk} 0.10476190 0.5076923 1.0121714
## [631] {Cheese, Meat} => {Bread} 0.14285714 0.4411765 0.8740289
## [632] {Bread, Meat} => {Cheese} 0.14285714 0.6923077 1.3802337
## [633] {Bread, Cheese} => {Meat} 0.14285714 0.6000000 1.2600000
## [634] {Meat} => {Cheese} 0.32380952 0.6800000 1.3556962
## [635] {Cheese} => {Meat} 0.32380952 0.6455696 1.3556962
## [636] {Meat} => {Bread} 0.20634921 0.4333333 0.8584906
## [637] {Bread} => {Meat} 0.20634921 0.4088050 0.8584906
## [638] {Milk} => {Meat} 0.24444444 0.4873418 1.0234177
## [639] {Meat} => {Milk} 0.24444444 0.5133333 1.0234177
## [640] {Cheese, Milk} => {Bread} 0.13015873 0.4270833 0.8461085
## [641] {Bread, Milk} => {Cheese} 0.13015873 0.4659091 0.9288694
## [642] {Bread, Cheese} => {Milk} 0.13015873 0.5466667 1.0898734
## [643] {Milk} => {Cheese} 0.30476190 0.6075949 1.2113443
## [644] {Cheese} => {Milk} 0.30476190 0.6075949 1.2113443
## [645] {Milk} => {Bread} 0.27936508 0.5569620 1.1034153
## [646] {Bread} => {Milk} 0.27936508 0.5534591 1.1034153
## [647] {Cheese} => {Bread} 0.23809524 0.4746835 0.9404108
## [648] {Bread} => {Cheese} 0.23809524 0.4716981 0.9404108
## itemset
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## [648] 200Saving the output
write(datarules, file = "datarules.csv", sep = ",", quote = TRUE, row.names = FALSE)What happens if we take the output as a data frame?
datarules_df <- as(datarules, "data.frame")
str(datarules_df)## 'data.frame': 1954 obs. of 6 variables:
## $ rules : chr "{Pencil} => {Diaper}" "{Diaper} => {Pencil}" "{Pencil} => {Bagel}" "{Bagel} => {Pencil}" ...
## $ support : num 0.171 0.171 0.159 0.159 0.165 ...
## $ confidence: num 0.474 0.422 0.439 0.373 0.456 ...
## $ coverage : num 0.362 0.406 0.362 0.425 0.362 ...
## $ lift : num 1.17 1.17 1.03 1.03 1.04 ...
## $ count : int 54 54 50 50 52 52 63 63 56 56 ...