setwd("D:\\R Files")
library(arules)
## Loading required package: Matrix
##
## Attaching package: 'arules'
## The following objects are masked from 'package:base':
##
## abbreviate, write
#load kosarak dat data
a=read.transactions("http://fimi.ua.ac.be/data/kosarak.dat")
## Warning in asMethod(object): removing duplicated items in transactions
itemFrequencyPlot(a,topN=20,type="absolute")
basket_rules <- apriori(a,parameter = list(sup = 0.03, conf = 0.01,target="rules"))
## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.01 0.1 1 none FALSE TRUE 5 0.03 1
## maxlen target ext
## 10 rules FALSE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 29700
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[41270 item(s), 990002 transaction(s)] done [2.34s].
## sorting and recoding items ... [16 item(s)] done [0.12s].
## creating transaction tree ... done [1.47s].
## checking subsets of size 1 2 3 4 done [0.00s].
## writing ... [137 rule(s)] done [0.00s].
## creating S4 object ... done [0.23s].
inspect(basket_rules)[1:10,]
## lhs rhs support confidence lift
## [1] {} => {294} 0.03257266 0.03257266 1.0000000
## [2] {} => {4} 0.07888570 0.07888570 1.0000000
## [3] {} => {55} 0.06607259 0.06607259 1.0000000
## [4] {} => {2} 0.04336052 0.04336052 1.0000000
## [5] {} => {138} 0.03548175 0.03548175 1.0000000
## [6] {} => {83} 0.03253731 0.03253731 1.0000000
## [7] {} => {77} 0.04389284 0.04389284 1.0000000
## [8] {} => {64} 0.04874940 0.04874940 1.0000000
## [9] {} => {27} 0.07286248 0.07286248 1.0000000
## [10] {} => {7} 0.08777558 0.08777558 1.0000000
## [11] {} => {148} 0.07062814 0.07062814 1.0000000
## [12] {} => {218} 0.08949275 0.08949275 1.0000000
## [13] {} => {1} 0.19951677 0.19951677 1.0000000
## [14] {} => {3} 0.45457585 0.45457585 1.0000000
## [15] {} => {11} 0.36774168 0.36774168 1.0000000
## [16] {} => {6} 0.60744726 0.60744726 1.0000000
## [17] {4} => {3} 0.03579589 0.45376903 0.9982251
## [18] {3} => {4} 0.03579589 0.07874569 0.9982251
## [19] {4} => {6} 0.04583526 0.58103384 0.9565174
## [20] {6} => {4} 0.04583526 0.07545554 0.9565174
## [21] {55} => {6} 0.03926760 0.59430991 0.9783729
## [22] {6} => {55} 0.03926760 0.06464363 0.9783729
## [23] {83} => {6} 0.03028580 0.93080219 1.5323177
## [24] {6} => {83} 0.03028580 0.04985749 1.5323177
## [25] {77} => {11} 0.03071610 0.69979749 1.9029594
## [26] {11} => {77} 0.03071610 0.08352629 1.9029594
## [27] {77} => {6} 0.03803427 0.86652552 1.4265033
## [28] {6} => {77} 0.03803427 0.06261328 1.4265033
## [29] {64} => {11} 0.03098681 0.63563466 1.7284814
## [30] {11} => {64} 0.03098681 0.08426243 1.7284814
## [31] {64} => {6} 0.04009790 0.82253118 1.3540784
## [32] {6} => {64} 0.04009790 0.06601050 1.3540784
## [33] {27} => {7} 0.04064133 0.55778135 6.3546302
## [34] {7} => {27} 0.04064133 0.46301411 6.3546302
## [35] {27} => {3} 0.03235044 0.44399312 0.9767196
## [36] {3} => {27} 0.03235044 0.07116621 0.9767196
## [37] {27} => {11} 0.04656859 0.63912995 1.7379862
## [38] {11} => {27} 0.04656859 0.12663398 1.7379862
## [39] {27} => {6} 0.06001806 0.82371697 1.3560304
## [40] {6} => {27} 0.06001806 0.09880374 1.3560304
## [41] {7} => {3} 0.03904942 0.44487790 0.9786659
## [42] {3} => {7} 0.03904942 0.08590297 0.9786659
## [43] {7} => {11} 0.05765039 0.65679302 1.7860173
## [44] {11} => {7} 0.05765039 0.15676871 1.7860173
## [45] {7} => {6} 0.07435339 0.84708509 1.3944998
## [46] {6} => {7} 0.07435339 0.12240303 1.3944998
## [47] {148} => {218} 0.05941705 0.84126598 9.4003816
## [48] {218} => {148} 0.05941705 0.66393147 9.4003816
## [49] {148} => {3} 0.03063630 0.43376906 0.9542281
## [50] {3} => {148} 0.03063630 0.06739536 0.9542281
## [51] {148} => {11} 0.05632211 0.79744573 2.1684943
## [52] {11} => {148} 0.05632211 0.15315672 2.1684943
## [53] {148} => {6} 0.06540391 0.92603186 1.5244646
## [54] {6} => {148} 0.06540391 0.10767010 1.5244646
## [55] {218} => {1} 0.03245145 0.36261541 1.8174683
## [56] {1} => {218} 0.03245145 0.16265024 1.8174683
## [57] {218} => {3} 0.03906356 0.43649970 0.9602351
## [58] {3} => {218} 0.03906356 0.08593408 0.9602351
## [59] {218} => {11} 0.06227866 0.69590736 1.8923810
## [60] {11} => {218} 0.06227866 0.16935437 1.8923810
## [61] {218} => {6} 0.07845944 0.87671279 1.4432739
## [62] {6} => {218} 0.07845944 0.12916255 1.4432739
## [63] {1} => {3} 0.08551498 0.42861048 0.9428800
## [64] {3} => {1} 0.08551498 0.18812037 0.9428800
## [65] {1} => {11} 0.09280991 0.46517350 1.2649464
## [66] {11} => {1} 0.09280991 0.25237801 1.2649464
## [67] {1} => {6} 0.13344721 0.66885208 1.1010867
## [68] {6} => {1} 0.13344721 0.21968525 1.1010867
## [69] {3} => {11} 0.16291482 0.35838864 0.9745663
## [70] {11} => {3} 0.16291482 0.44301430 0.9745663
## [71] {3} => {6} 0.26785804 0.58924830 0.9700403
## [72] {6} => {3} 0.26785804 0.44095688 0.9700403
## [73] {11} => {6} 0.32728520 0.88998668 1.4651258
## [74] {6} => {11} 0.32728520 0.53878784 1.4651258
## [75] {11,77} => {6} 0.03013125 0.98095958 1.6148885
## [76] {6,77} => {11} 0.03013125 0.79221331 2.1542658
## [77] {11,6} => {77} 0.03013125 0.09206421 2.0974766
## [78] {11,64} => {6} 0.03016661 0.97353066 1.6026587
## [79] {6,64} => {11} 0.03016661 0.75232385 2.0457943
## [80] {11,6} => {64} 0.03016661 0.09217223 1.8907358
## [81] {27,7} => {11} 0.03115044 0.76647198 2.0842673
## [82] {11,27} => {7} 0.03115044 0.66891525 7.6207443
## [83] {11,7} => {27} 0.03115044 0.54033360 7.4158004
## [84] {27,7} => {6} 0.03777467 0.92946440 1.5301154
## [85] {27,6} => {7} 0.03777467 0.62938840 7.1704271
## [86] {6,7} => {27} 0.03777467 0.50804239 6.9726201
## [87] {11,27} => {6} 0.04537668 0.97440514 1.6040983
## [88] {27,6} => {11} 0.04537668 0.75605036 2.0559278
## [89] {11,6} => {27} 0.04537668 0.13864567 1.9028404
## [90] {3,7} => {6} 0.03322721 0.85090147 1.4007825
## [91] {6,7} => {3} 0.03322721 0.44688222 0.9830751
## [92] {3,6} => {7} 0.03322721 0.12404782 1.4132384
## [93] {11,7} => {6} 0.05639888 0.97829134 1.6104959
## [94] {6,7} => {11} 0.05639888 0.75852466 2.0626562
## [95] {11,6} => {7} 0.05639888 0.17232333 1.9632264
## [96] {148,218} => {11} 0.05060394 0.85167367 2.3159563
## [97] {11,148} => {218} 0.05060394 0.89847379 10.0396267
## [98] {11,218} => {148} 0.05060394 0.81254055 11.5044874
## [99] {148,218} => {6} 0.05741201 0.96625470 1.5906808
## [100] {148,6} => {218} 0.05741201 0.87780695 9.8086936
## [101] {218,6} => {148} 0.05741201 0.73174123 10.3604771
## [102] {11,148} => {6} 0.05578777 0.99051274 1.6306152
## [103] {148,6} => {11} 0.05578777 0.85297297 2.3194895
## [104] {11,6} => {148} 0.05578777 0.17045612 2.4134307
## [105] {1,218} => {6} 0.03048681 0.93945902 1.5465689
## [106] {218,6} => {1} 0.03048681 0.38856775 1.9475443
## [107] {1,6} => {218} 0.03048681 0.22845594 2.5527872
## [108] {218,3} => {6} 0.03432114 0.87859747 1.4463766
## [109] {218,6} => {3} 0.03432114 0.43743804 0.9622993
## [110] {3,6} => {218} 0.03432114 0.12813183 1.4317566
## [111] {11,218} => {6} 0.06124230 0.98335928 1.6188390
## [112] {218,6} => {11} 0.06124230 0.78056003 2.1225770
## [113] {11,6} => {218} 0.06124230 0.18712212 2.0909194
## [114] {1,3} => {11} 0.04067467 0.47564375 1.2934181
## [115] {1,11} => {3} 0.04067467 0.43825777 0.9641026
## [116] {11,3} => {1} 0.04067467 0.24966829 1.2513649
## [117] {1,3} => {6} 0.05838574 0.68275455 1.1239734
## [118] {1,6} => {3} 0.05838574 0.43751940 0.9624783
## [119] {3,6} => {1} 0.05838574 0.21797270 1.0925031
## [120] {1,11} => {6} 0.08696144 0.93698439 1.5424951
## [121] {1,6} => {11} 0.08696144 0.65165427 1.7720435
## [122] {11,6} => {1} 0.08696144 0.26570539 1.3317446
## [123] {11,3} => {6} 0.14513304 0.89085227 1.4665508
## [124] {3,6} => {11} 0.14513304 0.54182819 1.4733935
## [125] {11,6} => {3} 0.14513304 0.44344517 0.9755141
## [126] {11,27,7} => {6} 0.03087570 0.99118000 1.6317137
## [127] {27,6,7} => {11} 0.03087570 0.81736503 2.2226608
## [128] {11,27,6} => {7} 0.03087570 0.68043096 7.7519392
## [129] {11,6,7} => {27} 0.03087570 0.54745231 7.5135011
## [130] {11,148,218} => {6} 0.05036960 0.99536908 1.6386099
## [131] {148,218,6} => {11} 0.05036960 0.87733559 2.3857388
## [132] {11,148,6} => {218} 0.05036960 0.90287887 10.0888495
## [133] {11,218,6} => {148} 0.05036960 0.82246413 11.6449920
## [134] {1,11,3} => {6} 0.03812417 0.93729512 1.5430066
## [135] {1,3,6} => {11} 0.03812417 0.65297049 1.7756227
## [136] {1,11,6} => {3} 0.03812417 0.43840310 0.9644223
## [137] {11,3,6} => {1} 0.03812417 0.26268426 1.3166024
## lhs rhs support confidence lift
## [1] {} => {294} 0.03257266 0.03257266 1
## [2] {} => {4} 0.07888570 0.07888570 1
## [3] {} => {55} 0.06607259 0.06607259 1
## [4] {} => {2} 0.04336052 0.04336052 1
## [5] {} => {138} 0.03548175 0.03548175 1
## [6] {} => {83} 0.03253731 0.03253731 1
## [7] {} => {77} 0.04389284 0.04389284 1
## [8] {} => {64} 0.04874940 0.04874940 1
## [9] {} => {27} 0.07286248 0.07286248 1
## [10] {} => {7} 0.08777558 0.08777558 1
basket_rules <- sort(basket_rules, by="lift")
library(arulesViz)
## Loading required package: grid
## Warning: failed to assign NativeSymbolInfo for lhs since lhs is already
## defined in the 'lazyeval' namespace
## Warning: failed to assign NativeSymbolInfo for rhs since rhs is already
## defined in the 'lazyeval' namespace
plot(basket_rules[1:10,])
plot(basket_rules[1:10,], method="graph", control=list(type="items"))
inspect(basket_rules)[1:10,]
## lhs rhs support confidence lift
## [1] {11,218,6} => {148} 0.05036960 0.82246413 11.6449920
## [2] {11,218} => {148} 0.05060394 0.81254055 11.5044874
## [3] {218,6} => {148} 0.05741201 0.73174123 10.3604771
## [4] {11,148,6} => {218} 0.05036960 0.90287887 10.0888495
## [5] {11,148} => {218} 0.05060394 0.89847379 10.0396267
## [6] {148,6} => {218} 0.05741201 0.87780695 9.8086936
## [7] {148} => {218} 0.05941705 0.84126598 9.4003816
## [8] {218} => {148} 0.05941705 0.66393147 9.4003816
## [9] {11,27,6} => {7} 0.03087570 0.68043096 7.7519392
## [10] {11,27} => {7} 0.03115044 0.66891525 7.6207443
## [11] {11,6,7} => {27} 0.03087570 0.54745231 7.5135011
## [12] {11,7} => {27} 0.03115044 0.54033360 7.4158004
## [13] {27,6} => {7} 0.03777467 0.62938840 7.1704271
## [14] {6,7} => {27} 0.03777467 0.50804239 6.9726201
## [15] {27} => {7} 0.04064133 0.55778135 6.3546302
## [16] {7} => {27} 0.04064133 0.46301411 6.3546302
## [17] {1,6} => {218} 0.03048681 0.22845594 2.5527872
## [18] {11,6} => {148} 0.05578777 0.17045612 2.4134307
## [19] {148,218,6} => {11} 0.05036960 0.87733559 2.3857388
## [20] {148,6} => {11} 0.05578777 0.85297297 2.3194895
## [21] {148,218} => {11} 0.05060394 0.85167367 2.3159563
## [22] {27,6,7} => {11} 0.03087570 0.81736503 2.2226608
## [23] {148} => {11} 0.05632211 0.79744573 2.1684943
## [24] {11} => {148} 0.05632211 0.15315672 2.1684943
## [25] {6,77} => {11} 0.03013125 0.79221331 2.1542658
## [26] {218,6} => {11} 0.06124230 0.78056003 2.1225770
## [27] {11,6} => {77} 0.03013125 0.09206421 2.0974766
## [28] {11,6} => {218} 0.06124230 0.18712212 2.0909194
## [29] {27,7} => {11} 0.03115044 0.76647198 2.0842673
## [30] {6,7} => {11} 0.05639888 0.75852466 2.0626562
## [31] {27,6} => {11} 0.04537668 0.75605036 2.0559278
## [32] {6,64} => {11} 0.03016661 0.75232385 2.0457943
## [33] {11,6} => {7} 0.05639888 0.17232333 1.9632264
## [34] {218,6} => {1} 0.03048681 0.38856775 1.9475443
## [35] {77} => {11} 0.03071610 0.69979749 1.9029594
## [36] {11} => {77} 0.03071610 0.08352629 1.9029594
## [37] {11,6} => {27} 0.04537668 0.13864567 1.9028404
## [38] {218} => {11} 0.06227866 0.69590736 1.8923810
## [39] {11} => {218} 0.06227866 0.16935437 1.8923810
## [40] {11,6} => {64} 0.03016661 0.09217223 1.8907358
## [41] {218} => {1} 0.03245145 0.36261541 1.8174683
## [42] {1} => {218} 0.03245145 0.16265024 1.8174683
## [43] {7} => {11} 0.05765039 0.65679302 1.7860173
## [44] {11} => {7} 0.05765039 0.15676871 1.7860173
## [45] {1,3,6} => {11} 0.03812417 0.65297049 1.7756227
## [46] {1,6} => {11} 0.08696144 0.65165427 1.7720435
## [47] {27} => {11} 0.04656859 0.63912995 1.7379862
## [48] {11} => {27} 0.04656859 0.12663398 1.7379862
## [49] {64} => {11} 0.03098681 0.63563466 1.7284814
## [50] {11} => {64} 0.03098681 0.08426243 1.7284814
## [51] {11,148,218} => {6} 0.05036960 0.99536908 1.6386099
## [52] {11,27,7} => {6} 0.03087570 0.99118000 1.6317137
## [53] {11,148} => {6} 0.05578777 0.99051274 1.6306152
## [54] {11,218} => {6} 0.06124230 0.98335928 1.6188390
## [55] {11,77} => {6} 0.03013125 0.98095958 1.6148885
## [56] {11,7} => {6} 0.05639888 0.97829134 1.6104959
## [57] {11,27} => {6} 0.04537668 0.97440514 1.6040983
## [58] {11,64} => {6} 0.03016661 0.97353066 1.6026587
## [59] {148,218} => {6} 0.05741201 0.96625470 1.5906808
## [60] {1,218} => {6} 0.03048681 0.93945902 1.5465689
## [61] {1,11,3} => {6} 0.03812417 0.93729512 1.5430066
## [62] {1,11} => {6} 0.08696144 0.93698439 1.5424951
## [63] {83} => {6} 0.03028580 0.93080219 1.5323177
## [64] {6} => {83} 0.03028580 0.04985749 1.5323177
## [65] {27,7} => {6} 0.03777467 0.92946440 1.5301154
## [66] {148} => {6} 0.06540391 0.92603186 1.5244646
## [67] {6} => {148} 0.06540391 0.10767010 1.5244646
## [68] {3,6} => {11} 0.14513304 0.54182819 1.4733935
## [69] {11,3} => {6} 0.14513304 0.89085227 1.4665508
## [70] {11} => {6} 0.32728520 0.88998668 1.4651258
## [71] {6} => {11} 0.32728520 0.53878784 1.4651258
## [72] {218,3} => {6} 0.03432114 0.87859747 1.4463766
## [73] {218} => {6} 0.07845944 0.87671279 1.4432739
## [74] {6} => {218} 0.07845944 0.12916255 1.4432739
## [75] {3,6} => {218} 0.03432114 0.12813183 1.4317566
## [76] {77} => {6} 0.03803427 0.86652552 1.4265033
## [77] {6} => {77} 0.03803427 0.06261328 1.4265033
## [78] {3,6} => {7} 0.03322721 0.12404782 1.4132384
## [79] {3,7} => {6} 0.03322721 0.85090147 1.4007825
## [80] {7} => {6} 0.07435339 0.84708509 1.3944998
## [81] {6} => {7} 0.07435339 0.12240303 1.3944998
## [82] {27} => {6} 0.06001806 0.82371697 1.3560304
## [83] {6} => {27} 0.06001806 0.09880374 1.3560304
## [84] {64} => {6} 0.04009790 0.82253118 1.3540784
## [85] {6} => {64} 0.04009790 0.06601050 1.3540784
## [86] {11,6} => {1} 0.08696144 0.26570539 1.3317446
## [87] {11,3,6} => {1} 0.03812417 0.26268426 1.3166024
## [88] {1,3} => {11} 0.04067467 0.47564375 1.2934181
## [89] {1} => {11} 0.09280991 0.46517350 1.2649464
## [90] {11} => {1} 0.09280991 0.25237801 1.2649464
## [91] {11,3} => {1} 0.04067467 0.24966829 1.2513649
## [92] {1,3} => {6} 0.05838574 0.68275455 1.1239734
## [93] {1} => {6} 0.13344721 0.66885208 1.1010867
## [94] {6} => {1} 0.13344721 0.21968525 1.1010867
## [95] {3,6} => {1} 0.05838574 0.21797270 1.0925031
## [96] {} => {294} 0.03257266 0.03257266 1.0000000
## [97] {} => {4} 0.07888570 0.07888570 1.0000000
## [98] {} => {55} 0.06607259 0.06607259 1.0000000
## [99] {} => {2} 0.04336052 0.04336052 1.0000000
## [100] {} => {138} 0.03548175 0.03548175 1.0000000
## [101] {} => {83} 0.03253731 0.03253731 1.0000000
## [102] {} => {77} 0.04389284 0.04389284 1.0000000
## [103] {} => {64} 0.04874940 0.04874940 1.0000000
## [104] {} => {27} 0.07286248 0.07286248 1.0000000
## [105] {} => {7} 0.08777558 0.08777558 1.0000000
## [106] {} => {148} 0.07062814 0.07062814 1.0000000
## [107] {} => {218} 0.08949275 0.08949275 1.0000000
## [108] {} => {1} 0.19951677 0.19951677 1.0000000
## [109] {} => {3} 0.45457585 0.45457585 1.0000000
## [110] {} => {11} 0.36774168 0.36774168 1.0000000
## [111] {} => {6} 0.60744726 0.60744726 1.0000000
## [112] {4} => {3} 0.03579589 0.45376903 0.9982251
## [113] {3} => {4} 0.03579589 0.07874569 0.9982251
## [114] {6,7} => {3} 0.03322721 0.44688222 0.9830751
## [115] {7} => {3} 0.03904942 0.44487790 0.9786659
## [116] {3} => {7} 0.03904942 0.08590297 0.9786659
## [117] {55} => {6} 0.03926760 0.59430991 0.9783729
## [118] {6} => {55} 0.03926760 0.06464363 0.9783729
## [119] {27} => {3} 0.03235044 0.44399312 0.9767196
## [120] {3} => {27} 0.03235044 0.07116621 0.9767196
## [121] {11,6} => {3} 0.14513304 0.44344517 0.9755141
## [122] {3} => {11} 0.16291482 0.35838864 0.9745663
## [123] {11} => {3} 0.16291482 0.44301430 0.9745663
## [124] {3} => {6} 0.26785804 0.58924830 0.9700403
## [125] {6} => {3} 0.26785804 0.44095688 0.9700403
## [126] {1,11,6} => {3} 0.03812417 0.43840310 0.9644223
## [127] {1,11} => {3} 0.04067467 0.43825777 0.9641026
## [128] {1,6} => {3} 0.05838574 0.43751940 0.9624783
## [129] {218,6} => {3} 0.03432114 0.43743804 0.9622993
## [130] {218} => {3} 0.03906356 0.43649970 0.9602351
## [131] {3} => {218} 0.03906356 0.08593408 0.9602351
## [132] {4} => {6} 0.04583526 0.58103384 0.9565174
## [133] {6} => {4} 0.04583526 0.07545554 0.9565174
## [134] {148} => {3} 0.03063630 0.43376906 0.9542281
## [135] {3} => {148} 0.03063630 0.06739536 0.9542281
## [136] {1} => {3} 0.08551498 0.42861048 0.9428800
## [137] {3} => {1} 0.08551498 0.18812037 0.9428800
## lhs rhs support confidence lift
## [1] {11,218,6} => {148} 0.05036960 0.8224641 11.644992
## [2] {11,218} => {148} 0.05060394 0.8125405 11.504487
## [3] {218,6} => {148} 0.05741201 0.7317412 10.360477
## [4] {11,148,6} => {218} 0.05036960 0.9028789 10.088849
## [5] {11,148} => {218} 0.05060394 0.8984738 10.039627
## [6] {148,6} => {218} 0.05741201 0.8778069 9.808694
## [7] {148} => {218} 0.05941705 0.8412660 9.400382
## [8] {218} => {148} 0.05941705 0.6639315 9.400382
## [9] {11,27,6} => {7} 0.03087570 0.6804310 7.751939
## [10] {11,27} => {7} 0.03115044 0.6689153 7.620744