Market Basket Analysis
Reading the data file
mydata<-read.csv("file:///C:/Users/badal/Desktop/datset_/Cosmetics.csv", colClasses = "factor", header = T)
head(mydata)## Trans. Bag Blush Nail.Polish Brushes Concealer Eyebrow.Pencils Bronzer
## 1 1 0 1 1 1 1 0 1
## 2 2 0 0 1 0 1 0 1
## 3 3 0 1 0 0 1 1 1
## 4 4 0 0 1 1 1 0 1
## 5 5 0 1 0 0 1 0 1
## 6 6 0 0 0 0 1 0 0
## Lip.liner Mascara Eye.shadow Foundation Lip.Gloss Lipstick Eyeliner
## 1 1 1 0 0 0 0 1
## 2 1 0 0 1 1 0 0
## 3 1 1 1 1 1 1 0
## 4 0 0 0 1 0 0 1
## 5 1 1 1 0 1 1 0
## 6 0 0 0 0 0 0 1#install.packages("arules")
library(arules)## Warning: package 'arules' was built under R version 3.6.2## Loading required package: Matrix##
## Attaching package: 'arules'## The following objects are masked from 'package:base':
##
## abbreviate, writeFinding association rules
rules <- apriori(mydata)## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.8 0.1 1 none FALSE TRUE 5 0.1 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: 100
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[1028 item(s), 1000 transaction(s)] done [0.00s].
## sorting and recoding items ... [26 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3 4 5 6 7 8 9 10## Warning in apriori(mydata): Mining stopped (maxlen reached). Only patterns
## up to a length of 10 returned!## done [0.02s].
## writing ... [68880 rule(s)] done [0.04s].
## creating S4 object ... done [0.03s].summary(rules)## set of 68880 rules
##
## rule length distribution (lhs + rhs):sizes
## 1 2 3 4 5 6 7 8 9 10
## 3 85 942 4350 10739 17062 18066 11996 4665 972
##
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.000 6.000 7.000 6.542 8.000 10.000
##
## summary of quality measures:
## support confidence lift count
## Min. :0.1000 Min. :0.8000 Min. :0.8781 Min. :100.0
## 1st Qu.:0.1150 1st Qu.:0.8667 1st Qu.:1.0389 1st Qu.:115.0
## Median :0.1370 Median :0.9453 Median :1.1565 Median :137.0
## Mean :0.1583 Mean :0.9259 Mean :1.2019 Mean :158.3
## 3rd Qu.:0.1770 3rd Qu.:0.9821 3rd Qu.:1.2438 3rd Qu.:177.0
## Max. :0.9580 Max. :1.0000 Max. :3.5714 Max. :958.0
##
## mining info:
## data ntransactions support confidence
## mydata 1000 0.1 0.8Rules with specified parameter valus
rules <- apriori(mydata,parameter = list(minlen=2, maxlen=10,supp=.7, conf=.8))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.8 0.1 1 none FALSE TRUE 5 0.7 2
## 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: 700
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[1028 item(s), 1000 transaction(s)] done [0.00s].
## sorting and recoding items ... [6 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3 done [0.00s].
## writing ... [15 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].inspect(rules)## lhs rhs support
## [1] {Nail.Polish=0} => {Brushes=0} 0.720
## [2] {Brushes=0} => {Nail.Polish=0} 0.720
## [3] {Lip.liner=0} => {Bag=0} 0.732
## [4] {Lip.liner=0} => {Eyebrow.Pencils=0} 0.734
## [5] {Brushes=0} => {Bag=0} 0.817
## [6] {Bag=0} => {Brushes=0} 0.817
## [7] {Brushes=0} => {Eyebrow.Pencils=0} 0.820
## [8] {Eyebrow.Pencils=0} => {Brushes=0} 0.820
## [9] {Bag=0} => {Eyebrow.Pencils=0} 0.909
## [10] {Eyebrow.Pencils=0} => {Bag=0} 0.909
## [11] {Bag=0,Lip.liner=0} => {Eyebrow.Pencils=0} 0.703
## [12] {Eyebrow.Pencils=0,Lip.liner=0} => {Bag=0} 0.703
## [13] {Bag=0,Brushes=0} => {Eyebrow.Pencils=0} 0.789
## [14] {Brushes=0,Eyebrow.Pencils=0} => {Bag=0} 0.789
## [15] {Bag=0,Eyebrow.Pencils=0} => {Brushes=0} 0.789
## confidence lift count
## [1] 1.0000000 1.175088 720
## [2] 0.8460635 1.175088 720
## [3] 0.9556136 1.010162 732
## [4] 0.9582245 1.000234 734
## [5] 0.9600470 1.014849 817
## [6] 0.8636364 1.014849 817
## [7] 0.9635723 1.005817 820
## [8] 0.8559499 1.005817 820
## [9] 0.9608879 1.003015 909
## [10] 0.9488518 1.003015 909
## [11] 0.9603825 1.002487 703
## [12] 0.9577657 1.012437 703
## [13] 0.9657283 1.008067 789
## [14] 0.9621951 1.017120 789
## [15] 0.8679868 1.019961 789Finding interesting rules-1
rules <- apriori(mydata, parameter = list(minlen =2, maxlen =3, conf = 0.7),
appearance = list(rhs=c("Foundation=1"), default= "lhs"))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.7 0.1 1 none FALSE TRUE 5 0.1 2
## maxlen target ext
## 3 rules FALSE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 100
##
## set item appearances ...[1 item(s)] done [0.00s].
## set transactions ...[1028 item(s), 1000 transaction(s)] done [0.00s].
## sorting and recoding items ... [26 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3## Warning in apriori(mydata, parameter = list(minlen = 2, maxlen = 3, conf =
## 0.7), : Mining stopped (maxlen reached). Only patterns up to a length of 3
## returned!## done [0.00s].
## writing ... [16 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].inspect(rules) ## lhs rhs support confidence
## [1] {Lip.Gloss=1} => {Foundation=1} 0.356 0.7265306
## [2] {Lip.Gloss=1,Lipstick=1} => {Foundation=1} 0.116 0.7341772
## [3] {Mascara=1,Lip.Gloss=1} => {Foundation=1} 0.130 0.7182320
## [4] {Eye.shadow=1,Lip.Gloss=1} => {Foundation=1} 0.146 0.7263682
## [5] {Lip.Gloss=1,Eyeliner=0} => {Foundation=1} 0.200 0.7604563
## [6] {Concealer=0,Lip.Gloss=1} => {Foundation=1} 0.215 0.7904412
## [7] {Eye.shadow=0,Lip.Gloss=1} => {Foundation=1} 0.210 0.7266436
## [8] {Blush=0,Lip.Gloss=1} => {Foundation=1} 0.237 0.7596154
## [9] {Mascara=0,Lip.Gloss=1} => {Foundation=1} 0.226 0.7313916
## [10] {Lip.Gloss=1,Lipstick=0} => {Foundation=1} 0.240 0.7228916
## [11] {Nail.Polish=0,Lip.Gloss=1} => {Foundation=1} 0.267 0.7500000
## [12] {Bronzer=0,Lip.Gloss=1} => {Foundation=1} 0.295 0.8452722
## [13] {Lip.liner=0,Lip.Gloss=1} => {Foundation=1} 0.310 0.8288770
## [14] {Brushes=0,Lip.Gloss=1} => {Foundation=1} 0.313 0.7417062
## [15] {Bag=0,Lip.Gloss=1} => {Foundation=1} 0.335 0.7282609
## [16] {Eyebrow.Pencils=0,Lip.Gloss=1} => {Foundation=1} 0.345 0.7278481
## lift count
## [1] 1.355468 356
## [2] 1.369734 116
## [3] 1.339985 130
## [4] 1.355164 146
## [5] 1.418762 200
## [6] 1.474704 215
## [7] 1.355678 210
## [8] 1.417193 237
## [9] 1.364537 226
## [10] 1.348678 240
## [11] 1.399254 267
## [12] 1.577000 295
## [13] 1.546412 310
## [14] 1.383780 313
## [15] 1.358696 335
## [16] 1.357926 345#install.packages("arulesViz")
library(arulesViz)## Warning: package 'arulesViz' was built under R version 3.6.2## Loading required package: grid## Registered S3 method overwritten by 'seriation':
## method from
## reorder.hclust gclusplot(rules)
plot(rules, method = "grouped")
plot(rules, method = "graph", control = list(type= "items"))## Warning: Unknown control parameters: type## Available control parameters (with default values):
## main = Graph for 16 rules
## nodeColors = c("#66CC6680", "#9999CC80")
## nodeCol = c("#EE0000FF", "#EE0303FF", "#EE0606FF", "#EE0909FF", "#EE0C0CFF", "#EE0F0FFF", "#EE1212FF", "#EE1515FF", "#EE1818FF", "#EE1B1BFF", "#EE1E1EFF", "#EE2222FF", "#EE2525FF", "#EE2828FF", "#EE2B2BFF", "#EE2E2EFF", "#EE3131FF", "#EE3434FF", "#EE3737FF", "#EE3A3AFF", "#EE3D3DFF", "#EE4040FF", "#EE4444FF", "#EE4747FF", "#EE4A4AFF", "#EE4D4DFF", "#EE5050FF", "#EE5353FF", "#EE5656FF", "#EE5959FF", "#EE5C5CFF", "#EE5F5FFF", "#EE6262FF", "#EE6666FF", "#EE6969FF", "#EE6C6CFF", "#EE6F6FFF", "#EE7272FF", "#EE7575FF", "#EE7878FF", "#EE7B7BFF", "#EE7E7EFF", "#EE8181FF", "#EE8484FF", "#EE8888FF", "#EE8B8BFF", "#EE8E8EFF", "#EE9191FF", "#EE9494FF", "#EE9797FF", "#EE9999FF", "#EE9B9BFF", "#EE9D9DFF", "#EE9F9FFF", "#EEA0A0FF", "#EEA2A2FF", "#EEA4A4FF", "#EEA5A5FF", "#EEA7A7FF", "#EEA9A9FF", "#EEABABFF", "#EEACACFF", "#EEAEAEFF", "#EEB0B0FF", "#EEB1B1FF", "#EEB3B3FF", "#EEB5B5FF", "#EEB7B7FF", "#EEB8B8FF", "#EEBABAFF", "#EEBCBCFF", "#EEBDBDFF", "#EEBFBFFF", "#EEC1C1FF", "#EEC3C3FF", "#EEC4C4FF", "#EEC6C6FF", "#EEC8C8FF", "#EEC9C9FF", "#EECBCBFF", "#EECDCDFF", "#EECFCFFF", "#EED0D0FF", "#EED2D2FF", "#EED4D4FF", "#EED5D5FF", "#EED7D7FF", "#EED9D9FF", "#EEDBDBFF", "#EEDCDCFF", "#EEDEDEFF", "#EEE0E0FF", "#EEE1E1FF", "#EEE3E3FF", "#EEE5E5FF", "#EEE7E7FF", "#EEE8E8FF", "#EEEAEAFF", "#EEECECFF", "#EEEEEEFF")
## edgeCol = c("#474747FF", "#494949FF", "#4B4B4BFF", "#4D4D4DFF", "#4F4F4FFF", "#515151FF", "#535353FF", "#555555FF", "#575757FF", "#595959FF", "#5B5B5BFF", "#5E5E5EFF", "#606060FF", "#626262FF", "#646464FF", "#666666FF", "#686868FF", "#6A6A6AFF", "#6C6C6CFF", "#6E6E6EFF", "#707070FF", "#727272FF", "#747474FF", "#767676FF", "#787878FF", "#7A7A7AFF", "#7C7C7CFF", "#7E7E7EFF", "#808080FF", "#828282FF", "#848484FF", "#868686FF", "#888888FF", "#8A8A8AFF", "#8C8C8CFF", "#8D8D8DFF", "#8F8F8FFF", "#919191FF", "#939393FF", "#959595FF", "#979797FF", "#999999FF", "#9A9A9AFF", "#9C9C9CFF", "#9E9E9EFF", "#A0A0A0FF", "#A2A2A2FF", "#A3A3A3FF", "#A5A5A5FF", "#A7A7A7FF", "#A9A9A9FF", "#AAAAAAFF", "#ACACACFF", "#AEAEAEFF", "#AFAFAFFF", "#B1B1B1FF", "#B3B3B3FF", "#B4B4B4FF", "#B6B6B6FF", "#B7B7B7FF", "#B9B9B9FF", "#BBBBBBFF", "#BCBCBCFF", "#BEBEBEFF", "#BFBFBFFF", "#C1C1C1FF", "#C2C2C2FF", "#C3C3C4FF", "#C5C5C5FF", "#C6C6C6FF", "#C8C8C8FF", "#C9C9C9FF", "#CACACAFF", "#CCCCCCFF", "#CDCDCDFF", "#CECECEFF", "#CFCFCFFF", "#D1D1D1FF", "#D2D2D2FF", "#D3D3D3FF", "#D4D4D4FF", "#D5D5D5FF", "#D6D6D6FF", "#D7D7D7FF", "#D8D8D8FF", "#D9D9D9FF", "#DADADAFF", "#DBDBDBFF", "#DCDCDCFF", "#DDDDDDFF", "#DEDEDEFF", "#DEDEDEFF", "#DFDFDFFF", "#E0E0E0FF", "#E0E0E0FF", "#E1E1E1FF", "#E1E1E1FF", "#E2E2E2FF", "#E2E2E2FF", "#E2E2E2FF")
## alpha = 0.5
## cex = 1
## itemLabels = TRUE
## labelCol = #000000B3
## measureLabels = FALSE
## precision = 3
## layout = NULL
## layoutParams = list()
## arrowSize = 0.5
## engine = igraph
## plot = TRUE
## plot_options = list()
## max = 100
## verbose = FALSE
rules <- apriori(mydata,parameter = list(minlen=2, maxlen=3,supp=.01, conf=.7),appearance=list(rhs=c("Foundation=1"),lhs=c("Bag=1", "Blush=1"),default="lhs"))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.7 0.1 1 none FALSE TRUE 5 0.01 2
## maxlen target ext
## 3 rules FALSE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 10
##
## set item appearances ...[3 item(s)] done [0.00s].
## set transactions ...[1028 item(s), 1000 transaction(s)] done [0.00s].
## sorting and recoding items ... [28 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3## Warning in apriori(mydata, parameter = list(minlen = 2, maxlen = 3, supp =
## 0.01, : Mining stopped (maxlen reached). Only patterns up to a length of 3
## returned!## done [0.00s].
## writing ... [19 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].inspect(rules)## lhs rhs support confidence
## [1] {Lip.Gloss=1} => {Foundation=1} 0.356 0.7265306
## [2] {Bag=1,Lip.Gloss=1} => {Foundation=1} 0.021 0.7000000
## [3] {Lip.Gloss=1,Lipstick=1} => {Foundation=1} 0.116 0.7341772
## [4] {Mascara=1,Lip.Gloss=1} => {Foundation=1} 0.130 0.7182320
## [5] {Mascara=1,Eye.shadow=0} => {Foundation=1} 0.026 0.7222222
## [6] {Eye.shadow=1,Lip.Gloss=1} => {Foundation=1} 0.146 0.7263682
## [7] {Mascara=0,Eye.shadow=1} => {Foundation=1} 0.045 0.7500000
## [8] {Lip.Gloss=1,Eyeliner=0} => {Foundation=1} 0.200 0.7604563
## [9] {Concealer=0,Lip.Gloss=1} => {Foundation=1} 0.215 0.7904412
## [10] {Eye.shadow=0,Lip.Gloss=1} => {Foundation=1} 0.210 0.7266436
## [11] {Blush=0,Lip.Gloss=1} => {Foundation=1} 0.237 0.7596154
## [12] {Mascara=0,Lip.Gloss=1} => {Foundation=1} 0.226 0.7313916
## [13] {Lip.Gloss=1,Lipstick=0} => {Foundation=1} 0.240 0.7228916
## [14] {Nail.Polish=0,Lip.Gloss=1} => {Foundation=1} 0.267 0.7500000
## [15] {Bronzer=0,Lip.Gloss=1} => {Foundation=1} 0.295 0.8452722
## [16] {Lip.liner=0,Lip.Gloss=1} => {Foundation=1} 0.310 0.8288770
## [17] {Brushes=0,Lip.Gloss=1} => {Foundation=1} 0.313 0.7417062
## [18] {Bag=0,Lip.Gloss=1} => {Foundation=1} 0.335 0.7282609
## [19] {Eyebrow.Pencils=0,Lip.Gloss=1} => {Foundation=1} 0.345 0.7278481
## lift count
## [1] 1.355468 356
## [2] 1.305970 21
## [3] 1.369734 116
## [4] 1.339985 130
## [5] 1.347430 26
## [6] 1.355164 146
## [7] 1.399254 45
## [8] 1.418762 200
## [9] 1.474704 215
## [10] 1.355678 210
## [11] 1.417193 237
## [12] 1.364537 226
## [13] 1.348678 240
## [14] 1.399254 267
## [15] 1.577000 295
## [16] 1.546412 310
## [17] 1.383780 313
## [18] 1.358696 335
## [19] 1.357926 345plot(rules, method = "graph", control = list(type= "items"))## Warning: Unknown control parameters: type## Available control parameters (with default values):
## main = Graph for 19 rules
## nodeColors = c("#66CC6680", "#9999CC80")
## nodeCol = c("#EE0000FF", "#EE0303FF", "#EE0606FF", "#EE0909FF", "#EE0C0CFF", "#EE0F0FFF", "#EE1212FF", "#EE1515FF", "#EE1818FF", "#EE1B1BFF", "#EE1E1EFF", "#EE2222FF", "#EE2525FF", "#EE2828FF", "#EE2B2BFF", "#EE2E2EFF", "#EE3131FF", "#EE3434FF", "#EE3737FF", "#EE3A3AFF", "#EE3D3DFF", "#EE4040FF", "#EE4444FF", "#EE4747FF", "#EE4A4AFF", "#EE4D4DFF", "#EE5050FF", "#EE5353FF", "#EE5656FF", "#EE5959FF", "#EE5C5CFF", "#EE5F5FFF", "#EE6262FF", "#EE6666FF", "#EE6969FF", "#EE6C6CFF", "#EE6F6FFF", "#EE7272FF", "#EE7575FF", "#EE7878FF", "#EE7B7BFF", "#EE7E7EFF", "#EE8181FF", "#EE8484FF", "#EE8888FF", "#EE8B8BFF", "#EE8E8EFF", "#EE9191FF", "#EE9494FF", "#EE9797FF", "#EE9999FF", "#EE9B9BFF", "#EE9D9DFF", "#EE9F9FFF", "#EEA0A0FF", "#EEA2A2FF", "#EEA4A4FF", "#EEA5A5FF", "#EEA7A7FF", "#EEA9A9FF", "#EEABABFF", "#EEACACFF", "#EEAEAEFF", "#EEB0B0FF", "#EEB1B1FF", "#EEB3B3FF", "#EEB5B5FF", "#EEB7B7FF", "#EEB8B8FF", "#EEBABAFF", "#EEBCBCFF", "#EEBDBDFF", "#EEBFBFFF", "#EEC1C1FF", "#EEC3C3FF", "#EEC4C4FF", "#EEC6C6FF", "#EEC8C8FF", "#EEC9C9FF", "#EECBCBFF", "#EECDCDFF", "#EECFCFFF", "#EED0D0FF", "#EED2D2FF", "#EED4D4FF", "#EED5D5FF", "#EED7D7FF", "#EED9D9FF", "#EEDBDBFF", "#EEDCDCFF", "#EEDEDEFF", "#EEE0E0FF", "#EEE1E1FF", "#EEE3E3FF", "#EEE5E5FF", "#EEE7E7FF", "#EEE8E8FF", "#EEEAEAFF", "#EEECECFF", "#EEEEEEFF")
## edgeCol = c("#474747FF", "#494949FF", "#4B4B4BFF", "#4D4D4DFF", "#4F4F4FFF", "#515151FF", "#535353FF", "#555555FF", "#575757FF", "#595959FF", "#5B5B5BFF", "#5E5E5EFF", "#606060FF", "#626262FF", "#646464FF", "#666666FF", "#686868FF", "#6A6A6AFF", "#6C6C6CFF", "#6E6E6EFF", "#707070FF", "#727272FF", "#747474FF", "#767676FF", "#787878FF", "#7A7A7AFF", "#7C7C7CFF", "#7E7E7EFF", "#808080FF", "#828282FF", "#848484FF", "#868686FF", "#888888FF", "#8A8A8AFF", "#8C8C8CFF", "#8D8D8DFF", "#8F8F8FFF", "#919191FF", "#939393FF", "#959595FF", "#979797FF", "#999999FF", "#9A9A9AFF", "#9C9C9CFF", "#9E9E9EFF", "#A0A0A0FF", "#A2A2A2FF", "#A3A3A3FF", "#A5A5A5FF", "#A7A7A7FF", "#A9A9A9FF", "#AAAAAAFF", "#ACACACFF", "#AEAEAEFF", "#AFAFAFFF", "#B1B1B1FF", "#B3B3B3FF", "#B4B4B4FF", "#B6B6B6FF", "#B7B7B7FF", "#B9B9B9FF", "#BBBBBBFF", "#BCBCBCFF", "#BEBEBEFF", "#BFBFBFFF", "#C1C1C1FF", "#C2C2C2FF", "#C3C3C4FF", "#C5C5C5FF", "#C6C6C6FF", "#C8C8C8FF", "#C9C9C9FF", "#CACACAFF", "#CCCCCCFF", "#CDCDCDFF", "#CECECEFF", "#CFCFCFFF", "#D1D1D1FF", "#D2D2D2FF", "#D3D3D3FF", "#D4D4D4FF", "#D5D5D5FF", "#D6D6D6FF", "#D7D7D7FF", "#D8D8D8FF", "#D9D9D9FF", "#DADADAFF", "#DBDBDBFF", "#DCDCDCFF", "#DDDDDDFF", "#DEDEDEFF", "#DEDEDEFF", "#DFDFDFFF", "#E0E0E0FF", "#E0E0E0FF", "#E1E1E1FF", "#E1E1E1FF", "#E2E2E2FF", "#E2E2E2FF", "#E2E2E2FF")
## alpha = 0.5
## cex = 1
## itemLabels = TRUE
## labelCol = #000000B3
## measureLabels = FALSE
## precision = 3
## layout = NULL
## layoutParams = list()
## arrowSize = 0.5
## engine = igraph
## plot = TRUE
## plot_options = list()
## max = 100
## verbose = FALSE
# Finding interesting rules-2
rules <- apriori(mydata,parameter = list(minlen=2, maxlen=5,supp=.1, conf=.5),appearance=list(rhs=c("Foundation=1"),lhs=c("Bag=1", "Blush=1", "Nail.Polish=1", "Brushes=1", "Concealer=1", "Eyebrow.Pencils=1", "Bronzer=1", "Lip.liner=1", "Mascara=1", "Eye.shadow=1","Lip.Gloss=1", "Lipstick=1", "Eyeliner=1"),default="none"))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.1 2
## maxlen target ext
## 5 rules FALSE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 100
##
## set item appearances ...[14 item(s)] done [0.00s].
## set transactions ...[14 item(s), 1000 transaction(s)] done [0.00s].
## sorting and recoding items ... [12 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3 4 done [0.00s].
## writing ... [22 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].quality(rules)<-round(quality(rules),digits=3)
rules.sorted <- sort(rules, by="lift")
inspect(rules)## lhs rhs support confidence lift count
## [1] {Lipstick=1} => {Foundation=1} 0.167 0.519 0.968 167
## [2] {Nail.Polish=1} => {Foundation=1} 0.143 0.511 0.953 143
## [3] {Blush=1} => {Foundation=1} 0.192 0.529 0.987 192
## [4] {Mascara=1} => {Foundation=1} 0.192 0.538 1.003 192
## [5] {Eye.shadow=1} => {Foundation=1} 0.211 0.554 1.033 211
## [6] {Eyeliner=1} => {Foundation=1} 0.238 0.521 0.972 238
## [7] {Lip.Gloss=1} => {Foundation=1} 0.356 0.727 1.355 356
## [8] {Concealer=1} => {Foundation=1} 0.231 0.523 0.975 231
## [9] {Lip.Gloss=1,
## Lipstick=1} => {Foundation=1} 0.116 0.734 1.370 116
## [10] {Blush=1,
## Mascara=1} => {Foundation=1} 0.101 0.549 1.024 101
## [11] {Blush=1,
## Eye.shadow=1} => {Foundation=1} 0.100 0.549 1.025 100
## [12] {Blush=1,
## Lip.Gloss=1} => {Foundation=1} 0.119 0.669 1.247 119
## [13] {Blush=1,
## Concealer=1} => {Foundation=1} 0.115 0.523 0.975 115
## [14] {Mascara=1,
## Eye.shadow=1} => {Foundation=1} 0.166 0.517 0.965 166
## [15] {Mascara=1,
## Lip.Gloss=1} => {Foundation=1} 0.130 0.718 1.340 130
## [16] {Concealer=1,
## Mascara=1} => {Foundation=1} 0.107 0.525 0.979 107
## [17] {Eye.shadow=1,
## Lip.Gloss=1} => {Foundation=1} 0.146 0.726 1.355 146
## [18] {Concealer=1,
## Eye.shadow=1} => {Foundation=1} 0.104 0.517 0.965 104
## [19] {Lip.Gloss=1,
## Eyeliner=1} => {Foundation=1} 0.156 0.687 1.282 156
## [20] {Concealer=1,
## Eyeliner=1} => {Foundation=1} 0.152 0.512 0.955 152
## [21] {Concealer=1,
## Lip.Gloss=1} => {Foundation=1} 0.141 0.647 1.207 141
## [22] {Mascara=1,
## Eye.shadow=1,
## Lip.Gloss=1} => {Foundation=1} 0.111 0.703 1.311 111plot(rules,method="graph",control=list(type="items"))## Warning: Unknown control parameters: type## Available control parameters (with default values):
## main = Graph for 22 rules
## nodeColors = c("#66CC6680", "#9999CC80")
## nodeCol = c("#EE0000FF", "#EE0303FF", "#EE0606FF", "#EE0909FF", "#EE0C0CFF", "#EE0F0FFF", "#EE1212FF", "#EE1515FF", "#EE1818FF", "#EE1B1BFF", "#EE1E1EFF", "#EE2222FF", "#EE2525FF", "#EE2828FF", "#EE2B2BFF", "#EE2E2EFF", "#EE3131FF", "#EE3434FF", "#EE3737FF", "#EE3A3AFF", "#EE3D3DFF", "#EE4040FF", "#EE4444FF", "#EE4747FF", "#EE4A4AFF", "#EE4D4DFF", "#EE5050FF", "#EE5353FF", "#EE5656FF", "#EE5959FF", "#EE5C5CFF", "#EE5F5FFF", "#EE6262FF", "#EE6666FF", "#EE6969FF", "#EE6C6CFF", "#EE6F6FFF", "#EE7272FF", "#EE7575FF", "#EE7878FF", "#EE7B7BFF", "#EE7E7EFF", "#EE8181FF", "#EE8484FF", "#EE8888FF", "#EE8B8BFF", "#EE8E8EFF", "#EE9191FF", "#EE9494FF", "#EE9797FF", "#EE9999FF", "#EE9B9BFF", "#EE9D9DFF", "#EE9F9FFF", "#EEA0A0FF", "#EEA2A2FF", "#EEA4A4FF", "#EEA5A5FF", "#EEA7A7FF", "#EEA9A9FF", "#EEABABFF", "#EEACACFF", "#EEAEAEFF", "#EEB0B0FF", "#EEB1B1FF", "#EEB3B3FF", "#EEB5B5FF", "#EEB7B7FF", "#EEB8B8FF", "#EEBABAFF", "#EEBCBCFF", "#EEBDBDFF", "#EEBFBFFF", "#EEC1C1FF", "#EEC3C3FF", "#EEC4C4FF", "#EEC6C6FF", "#EEC8C8FF", "#EEC9C9FF", "#EECBCBFF", "#EECDCDFF", "#EECFCFFF", "#EED0D0FF", "#EED2D2FF", "#EED4D4FF", "#EED5D5FF", "#EED7D7FF", "#EED9D9FF", "#EEDBDBFF", "#EEDCDCFF", "#EEDEDEFF", "#EEE0E0FF", "#EEE1E1FF", "#EEE3E3FF", "#EEE5E5FF", "#EEE7E7FF", "#EEE8E8FF", "#EEEAEAFF", "#EEECECFF", "#EEEEEEFF")
## edgeCol = c("#474747FF", "#494949FF", "#4B4B4BFF", "#4D4D4DFF", "#4F4F4FFF", "#515151FF", "#535353FF", "#555555FF", "#575757FF", "#595959FF", "#5B5B5BFF", "#5E5E5EFF", "#606060FF", "#626262FF", "#646464FF", "#666666FF", "#686868FF", "#6A6A6AFF", "#6C6C6CFF", "#6E6E6EFF", "#707070FF", "#727272FF", "#747474FF", "#767676FF", "#787878FF", "#7A7A7AFF", "#7C7C7CFF", "#7E7E7EFF", "#808080FF", "#828282FF", "#848484FF", "#868686FF", "#888888FF", "#8A8A8AFF", "#8C8C8CFF", "#8D8D8DFF", "#8F8F8FFF", "#919191FF", "#939393FF", "#959595FF", "#979797FF", "#999999FF", "#9A9A9AFF", "#9C9C9CFF", "#9E9E9EFF", "#A0A0A0FF", "#A2A2A2FF", "#A3A3A3FF", "#A5A5A5FF", "#A7A7A7FF", "#A9A9A9FF", "#AAAAAAFF", "#ACACACFF", "#AEAEAEFF", "#AFAFAFFF", "#B1B1B1FF", "#B3B3B3FF", "#B4B4B4FF", "#B6B6B6FF", "#B7B7B7FF", "#B9B9B9FF", "#BBBBBBFF", "#BCBCBCFF", "#BEBEBEFF", "#BFBFBFFF", "#C1C1C1FF", "#C2C2C2FF", "#C3C3C4FF", "#C5C5C5FF", "#C6C6C6FF", "#C8C8C8FF", "#C9C9C9FF", "#CACACAFF", "#CCCCCCFF", "#CDCDCDFF", "#CECECEFF", "#CFCFCFFF", "#D1D1D1FF", "#D2D2D2FF", "#D3D3D3FF", "#D4D4D4FF", "#D5D5D5FF", "#D6D6D6FF", "#D7D7D7FF", "#D8D8D8FF", "#D9D9D9FF", "#DADADAFF", "#DBDBDBFF", "#DCDCDCFF", "#DDDDDDFF", "#DEDEDEFF", "#DEDEDEFF", "#DFDFDFFF", "#E0E0E0FF", "#E0E0E0FF", "#E1E1E1FF", "#E1E1E1FF", "#E2E2E2FF", "#E2E2E2FF", "#E2E2E2FF")
## alpha = 0.5
## cex = 1
## itemLabels = TRUE
## labelCol = #000000B3
## measureLabels = FALSE
## precision = 3
## layout = NULL
## layoutParams = list()
## arrowSize = 0.5
## engine = igraph
## plot = TRUE
## plot_options = list()
## max = 100
## verbose = FALSE
Finding redundancy
redundant <- is.redundant(rules, measure="confidence")
which(redundant)## [1] 11 12 13 14 15 16 17 18 19 20 21 22rules.pruned <- rules[!redundant]
rules.pruned <- sort(rules.pruned, by="lift")
inspect(rules.pruned)## lhs rhs support confidence lift
## [1] {Lip.Gloss=1,Lipstick=1} => {Foundation=1} 0.116 0.734 1.370
## [2] {Lip.Gloss=1} => {Foundation=1} 0.356 0.727 1.355
## [3] {Eye.shadow=1} => {Foundation=1} 0.211 0.554 1.033
## [4] {Blush=1,Mascara=1} => {Foundation=1} 0.101 0.549 1.024
## [5] {Mascara=1} => {Foundation=1} 0.192 0.538 1.003
## [6] {Blush=1} => {Foundation=1} 0.192 0.529 0.987
## [7] {Concealer=1} => {Foundation=1} 0.231 0.523 0.975
## [8] {Eyeliner=1} => {Foundation=1} 0.238 0.521 0.972
## [9] {Lipstick=1} => {Foundation=1} 0.167 0.519 0.968
## [10] {Nail.Polish=1} => {Foundation=1} 0.143 0.511 0.953
## count
## [1] 116
## [2] 356
## [3] 211
## [4] 101
## [5] 192
## [6] 192
## [7] 231
## [8] 238
## [9] 167
## [10] 143Graphs and Charts
plot(rules.pruned,method="graph",control=list(type="items"))## Warning: Unknown control parameters: type## Available control parameters (with default values):
## main = Graph for 10 rules
## nodeColors = c("#66CC6680", "#9999CC80")
## nodeCol = c("#EE0000FF", "#EE0303FF", "#EE0606FF", "#EE0909FF", "#EE0C0CFF", "#EE0F0FFF", "#EE1212FF", "#EE1515FF", "#EE1818FF", "#EE1B1BFF", "#EE1E1EFF", "#EE2222FF", "#EE2525FF", "#EE2828FF", "#EE2B2BFF", "#EE2E2EFF", "#EE3131FF", "#EE3434FF", "#EE3737FF", "#EE3A3AFF", "#EE3D3DFF", "#EE4040FF", "#EE4444FF", "#EE4747FF", "#EE4A4AFF", "#EE4D4DFF", "#EE5050FF", "#EE5353FF", "#EE5656FF", "#EE5959FF", "#EE5C5CFF", "#EE5F5FFF", "#EE6262FF", "#EE6666FF", "#EE6969FF", "#EE6C6CFF", "#EE6F6FFF", "#EE7272FF", "#EE7575FF", "#EE7878FF", "#EE7B7BFF", "#EE7E7EFF", "#EE8181FF", "#EE8484FF", "#EE8888FF", "#EE8B8BFF", "#EE8E8EFF", "#EE9191FF", "#EE9494FF", "#EE9797FF", "#EE9999FF", "#EE9B9BFF", "#EE9D9DFF", "#EE9F9FFF", "#EEA0A0FF", "#EEA2A2FF", "#EEA4A4FF", "#EEA5A5FF", "#EEA7A7FF", "#EEA9A9FF", "#EEABABFF", "#EEACACFF", "#EEAEAEFF", "#EEB0B0FF", "#EEB1B1FF", "#EEB3B3FF", "#EEB5B5FF", "#EEB7B7FF", "#EEB8B8FF", "#EEBABAFF", "#EEBCBCFF", "#EEBDBDFF", "#EEBFBFFF", "#EEC1C1FF", "#EEC3C3FF", "#EEC4C4FF", "#EEC6C6FF", "#EEC8C8FF", "#EEC9C9FF", "#EECBCBFF", "#EECDCDFF", "#EECFCFFF", "#EED0D0FF", "#EED2D2FF", "#EED4D4FF", "#EED5D5FF", "#EED7D7FF", "#EED9D9FF", "#EEDBDBFF", "#EEDCDCFF", "#EEDEDEFF", "#EEE0E0FF", "#EEE1E1FF", "#EEE3E3FF", "#EEE5E5FF", "#EEE7E7FF", "#EEE8E8FF", "#EEEAEAFF", "#EEECECFF", "#EEEEEEFF")
## edgeCol = c("#474747FF", "#494949FF", "#4B4B4BFF", "#4D4D4DFF", "#4F4F4FFF", "#515151FF", "#535353FF", "#555555FF", "#575757FF", "#595959FF", "#5B5B5BFF", "#5E5E5EFF", "#606060FF", "#626262FF", "#646464FF", "#666666FF", "#686868FF", "#6A6A6AFF", "#6C6C6CFF", "#6E6E6EFF", "#707070FF", "#727272FF", "#747474FF", "#767676FF", "#787878FF", "#7A7A7AFF", "#7C7C7CFF", "#7E7E7EFF", "#808080FF", "#828282FF", "#848484FF", "#868686FF", "#888888FF", "#8A8A8AFF", "#8C8C8CFF", "#8D8D8DFF", "#8F8F8FFF", "#919191FF", "#939393FF", "#959595FF", "#979797FF", "#999999FF", "#9A9A9AFF", "#9C9C9CFF", "#9E9E9EFF", "#A0A0A0FF", "#A2A2A2FF", "#A3A3A3FF", "#A5A5A5FF", "#A7A7A7FF", "#A9A9A9FF", "#AAAAAAFF", "#ACACACFF", "#AEAEAEFF", "#AFAFAFFF", "#B1B1B1FF", "#B3B3B3FF", "#B4B4B4FF", "#B6B6B6FF", "#B7B7B7FF", "#B9B9B9FF", "#BBBBBBFF", "#BCBCBCFF", "#BEBEBEFF", "#BFBFBFFF", "#C1C1C1FF", "#C2C2C2FF", "#C3C3C4FF", "#C5C5C5FF", "#C6C6C6FF", "#C8C8C8FF", "#C9C9C9FF", "#CACACAFF", "#CCCCCCFF", "#CDCDCDFF", "#CECECEFF", "#CFCFCFFF", "#D1D1D1FF", "#D2D2D2FF", "#D3D3D3FF", "#D4D4D4FF", "#D5D5D5FF", "#D6D6D6FF", "#D7D7D7FF", "#D8D8D8FF", "#D9D9D9FF", "#DADADAFF", "#DBDBDBFF", "#DCDCDCFF", "#DDDDDDFF", "#DEDEDEFF", "#DEDEDEFF", "#DFDFDFFF", "#E0E0E0FF", "#E0E0E0FF", "#E1E1E1FF", "#E1E1E1FF", "#E2E2E2FF", "#E2E2E2FF", "#E2E2E2FF")
## alpha = 0.5
## cex = 1
## itemLabels = TRUE
## labelCol = #000000B3
## measureLabels = FALSE
## precision = 3
## layout = NULL
## layoutParams = list()
## arrowSize = 0.5
## engine = igraph
## plot = TRUE
## plot_options = list()
## max = 100
## verbose = FALSE