apriori 28.6 anh Phong chi
Hoang Linh Thi Le
2025-06-29
###Gọi các gói phần mềm
##đọc dữ liệu
dat <- read.transactions("C:\\Users\\lehoa\\Desktop\\a Phong\\28.6 machine learning\\AR-thongkinh.csv", format = "basket", sep = ",")#Mô tả dữ liệu
dim(dat)## [1] 109 148itemLabels(dat)## [1] "Agiao" "Bachbiendau"
## [3] "Bachduong" "Bachgioitu"
## [5] "Bachlinh" "Bachqua"
## [7] "Bachthuoc" "Bachtruat"
## [9] "Bakich" "Banha"
## [11] "Baokhuong" "Biendau"
## [13] "Boconganh" "Bocotchi"
## [15] "Bohoang" "Boimau"
## [17] "Camthao" "Cankhuong"
## [19] "CanThankhuyhu" "Canuatkhitrehuyetu"
## [21] "Canuattyhu" "Caoluongkhuong"
## [23] "Catcan" "Catcanh"
## [25] "Caudang" "Cocnha"
## [27] "Cuuhuongtrung" "Cuutatung"
## [29] "Chichthao" "Chitu"
## [31] "Chithuc" "Chixac"
## [33] "Daigiathach" "Daitao"
## [35] "Daitaoqua" "Damduonghoac"
## [37] "Danbi" "Dansam"
## [39] "Dangsam" "Daonhan"
## [41] "Dialong" "Dienhosach"
## [43] "Donbi" "Dotrong"
## [45] "Duonghuhanngung" "Duongquy"
## [47] "Hadiep" "Haiphieutieu"
## [49] "Hakhothao" "Hanngunghuyetu"
## [51] "Hanthapngungtre" "Hauphac"
## [53] "Hoangba" "Hoangcam"
## [55] "Hoangky" "Hoanglien"
## [57] "Holoba" "Honghoa"
## [59] "Huhan" "Huhanhuyetu"
## [61] "Huongphu" "HuyethukhitreHatieuhuhan"
## [63] "Ichmau" "Ichmauthao"
## [65] "Kehuyetdang" "Kenoikim"
## [67] "KTHUHNHU" "KhihuyetluonghuHatieuhuhan"
## [69] "Khitrehuyetu" "Kholuyentu"
## [71] "Khonthao" "Khuonghoang"
## [73] "Lechihach" "Lientu"
## [75] "Linhchi" "Locgiac"
## [77] "Luukyno" "Machmon"
## [79] "Mahoang" "Maule"
## [81] "Mocqua" "Mocthong"
## [83] "Mochuong" "Motduoc"
## [85] "Ngaidiep" "Ngatruat"
## [87] "Ngocong" "Ngothudu"
## [89] "Ngulinhchi" "Nguutat"
## [91] "Nhamda" "Nhansam"
## [93] "Nhansm" "Nhucqu"
## [95] "Nhucque" "Nhucthungdung"
## [97] "Nhuhuong" "Oduoc"
## [99] "Omai" "Phapbanha"
## [101] "Phutieumach" "Phutu"
## [103] "Quathach" "Quechi"
## [105] "Quygiap" "Saiho"
## [107] "Sanhan" "Sinhdia"
## [109] "Sinhkhuong" "Sonchi"
## [111] "Sonduoc" "Sonthu"
## [113] "Sonthudu" "Sotuco"
## [115] "Tamlang" "Tamthat"
## [117] "Tangkysinh" "Taonhan"
## [119] "Tetan" "Tieuhoihuong"
## [121] "Tieuhoihuongcai" "Tieumach"
## [123] "Tuboixi" "Tucdoan"
## [125] "Tuthachanh" "Tyhuhanthap"
## [127] "Tyqualac" "Thankhuc"
## [129] "Thanhbi" "Thienhoaphan"
## [131] "Thomiettrung" "Thongbach"
## [133] "Thongthao" "Thophuclinh"
## [135] "Thotytu" "Thucdia"
## [137] "thumn" "Thuongtruat"
## [139] "Trachlan" "Trachta"
## [141] "Tramhuong" "Tranbi"
## [143] "Uatkim" "Unhiethoket"
## [145] "Xichthuoc" "Xuyenkhung"
## [147] "Xuyenluyentu" "Ydi"summary(dat)## transactions as itemMatrix in sparse format with
## 109 rows (elements/itemsets/transactions) and
## 148 columns (items) and a density of 0.08225886
##
## most frequent items:
## Duongquy Xuyenkhung Dienhosach Bachthuoc Hanngunghuyetu
## 91 81 64 60 47
## (Other)
## 984
##
## element (itemset/transaction) length distribution:
## sizes
## 2 3 5 6 7 8 9 10 11 12 13 14 15 16 17 19
## 1 1 1 1 3 4 3 4 22 16 21 14 7 6 4 1
##
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.00 11.00 12.00 12.17 14.00 19.00
##
## includes extended item information - examples:
## labels
## 1 Agiao
## 2 Bachbiendau
## 3 Bachduongdisplay.brewer.all()
arules::itemFrequencyPlot(dat, topN = 20, col = brewer.pal(8, 'Pastel2'), main = 'Relative Item Frequency Plot', type = "relative", ylab = "Item Frequency (Relative)")
##Kiểm tra bộ dữ liệu phù hợp cho AR
sparsity <- 1 - (sum(as(dat, "ngCMatrix")) / (nrow(dat) * ncol(dat)))
cat("Sparsity của dữ liệu là:", round(sparsity * 100, 2), "%\n")## Sparsity của dữ liệu là: 91.77 %#Xác định ngưỡng support
rules <- apriori(dat, parameter = list(support = 0.01, confidence = 0.5))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.01 1
## 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 ...[148 item(s), 109 transaction(s)] done [0.00s].
## sorting and recoding items ... [89 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(dat, parameter = list(support = 0.01, confidence = 0.5)):
## Mining stopped (maxlen reached). Only patterns up to a length of 10 returned!## done [0.03s].
## writing ... [427294 rule(s)] done [0.08s].
## creating S4 object ... done [0.10s].rel_sup_rules <- quality(rules)$support
summary(rel_sup_rules)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.01835 0.01835 0.01835 0.02381 0.01835 0.83486hist(rel_sup_rules, breaks = 50, col = "skyblue", main = "Histogram of Rule Support", xlab = "Support")
#Xây dựng quy luật liên kết chung
rules <- apriori(dat, parameter = list(supp=0.03, conf=0.5, maxlen=5, target= "rules"))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.03 1
## maxlen target ext
## 5 rules TRUE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 3
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[148 item(s), 109 transaction(s)] done [0.00s].
## sorting and recoding items ... [59 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3 4 5## Warning in apriori(dat, parameter = list(supp = 0.03, conf = 0.5, maxlen = 5, :
## Mining stopped (maxlen reached). Only patterns up to a length of 5 returned!## done [0.00s].
## writing ... [22125 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].inspect(sort(rules, by = 'confidence')[1:20])## lhs rhs support confidence coverage lift
## [1] {Catcanh} => {Xuyenkhung} 0.03669725 1 0.03669725 1.345679
## [2] {Huhan} => {Duongquy} 0.03669725 1 0.03669725 1.197802
## [3] {Trachta} => {Bachlinh} 0.05504587 1 0.05504587 9.083333
## [4] {Trachta} => {Bachtruat} 0.05504587 1 0.05504587 7.785714
## [5] {Trachta} => {Bachthuoc} 0.05504587 1 0.05504587 1.816667
## [6] {Trachta} => {Xuyenkhung} 0.05504587 1 0.05504587 1.345679
## [7] {Trachta} => {Duongquy} 0.05504587 1 0.05504587 1.197802
## [8] {Nhansam} => {Donbi} 0.04587156 1 0.04587156 6.055556
## [9] {Tranbi} => {Xuyenkhung} 0.04587156 1 0.04587156 1.345679
## [10] {Tranbi} => {Duongquy} 0.04587156 1 0.04587156 1.197802
## [11] {Uatkim} => {Huongphu} 0.04587156 1 0.04587156 2.595238
## [12] {Uatkim} => {Duongquy} 0.04587156 1 0.04587156 1.197802
## [13] {Baokhuong} => {Dienhosach} 0.05504587 1 0.05504587 1.703125
## [14] {Baokhuong} => {Xuyenkhung} 0.05504587 1 0.05504587 1.345679
## [15] {Baokhuong} => {Duongquy} 0.05504587 1 0.05504587 1.197802
## [16] {Thanhbi} => {Duongquy} 0.05504587 1 0.05504587 1.197802
## [17] {Nhuhuong} => {Motduoc} 0.05504587 1 0.05504587 4.192308
## [18] {Nhuhuong} => {Xuyenkhung} 0.05504587 1 0.05504587 1.345679
## [19] {Nhuhuong} => {Duongquy} 0.05504587 1 0.05504587 1.197802
## [20] {Ngatruat} => {Hanngunghuyetu} 0.06422018 1 0.06422018 2.319149
## count
## [1] 4
## [2] 4
## [3] 6
## [4] 6
## [5] 6
## [6] 6
## [7] 6
## [8] 5
## [9] 5
## [10] 5
## [11] 5
## [12] 5
## [13] 6
## [14] 6
## [15] 6
## [16] 6
## [17] 6
## [18] 6
## [19] 6
## [20] 7subrule <- head(rules , n = 5, by = "confidence")plot(subrule, method = "graph", engine = "htmlwidget")#Chọn luật mạnh
library(arules)
n <- length(dat)
K <- 5
folds <- sample(rep(1:K, length.out = n))
results <- data.frame(Fold = 1:K, NumRules = NA, Accuracy = NA)
for (k in 1:K) {
test_idx <- which(folds == k)
train_data <- dat[-test_idx]
test_data <- dat[test_idx]
rules <- apriori(train_data, parameter = list(supp = 0.03, conf = 0.5, target = "rules"))
rhs_labels <- labels(rhs(rules))
rhs_items <- gsub("[\\{\\}]", "", rhs_labels)
rhs_support <- itemFrequency(train_data)[rhs_items]
added_value <- quality(rules)$confidence - rhs_support
quality(rules)$addedValue <- added_value
good_rules <- subset(rules,
subset = support >= 0.08 &
confidence >= 0.95 &
lift >= 5 &
addedValue >= 0.85)
if (length(good_rules) > 0) {
matched <- is.subset(lhs(good_rules), test_data)
rule_covered <- rowSums(matched) > 0
acc <- mean(rule_covered)
} else {
acc <- NA
}
results$NumRules[k] <- length(good_rules)
results$Accuracy[k] <- acc
}## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.03 1
## 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: 2
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[135 item(s), 87 transaction(s)] done [0.00s].
## sorting and recoding items ... [64 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(train_data, parameter = list(supp = 0.03, conf = 0.5, :
## Mining stopped (maxlen reached). Only patterns up to a length of 10 returned!## done [0.00s].
## writing ... [76841 rule(s)] done [0.01s].
## creating S4 object ... done [0.02s].
## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.03 1
## 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: 2
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[134 item(s), 87 transaction(s)] done [0.00s].
## sorting and recoding items ... [71 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(train_data, parameter = list(supp = 0.03, conf = 0.5, :
## Mining stopped (maxlen reached). Only patterns up to a length of 10 returned!## done [0.00s].
## writing ... [60302 rule(s)] done [0.00s].
## creating S4 object ... done [0.01s].
## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.03 1
## 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: 2
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[131 item(s), 87 transaction(s)] done [0.00s].
## sorting and recoding items ... [66 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(train_data, parameter = list(supp = 0.03, conf = 0.5, :
## Mining stopped (maxlen reached). Only patterns up to a length of 10 returned!## done [0.00s].
## writing ... [83370 rule(s)] done [0.01s].
## creating S4 object ... done [0.02s].
## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.03 1
## 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: 2
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[143 item(s), 87 transaction(s)] done [0.00s].
## sorting and recoding items ... [66 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(train_data, parameter = list(supp = 0.03, conf = 0.5, :
## Mining stopped (maxlen reached). Only patterns up to a length of 10 returned!## done [0.00s].
## writing ... [61587 rule(s)] done [0.01s].
## creating S4 object ... done [0.01s].
## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.5 0.1 1 none FALSE TRUE 5 0.03 1
## 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: 2
##
## set item appearances ...[0 item(s)] done [0.00s].
## set transactions ...[133 item(s), 88 transaction(s)] done [0.00s].
## sorting and recoding items ... [65 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(train_data, parameter = list(supp = 0.03, conf = 0.5, :
## Mining stopped (maxlen reached). Only patterns up to a length of 10 returned!## done [0.00s].
## writing ... [78421 rule(s)] done [0.01s].
## creating S4 object ... done [0.01s].print(results)## Fold NumRules Accuracy
## 1 1 4 1.0000000
## 2 2 92 1.0000000
## 3 3 791 0.1517067
## 4 4 125 1.0000000
## 5 5 55 1.0000000cat("Trung bình số luật:", mean(results$NumRules, na.rm = TRUE), "\n")## Trung bình số luật: 213.4cat("Độ chính xác trung bình:", round(mean(results$Accuracy, na.rm = TRUE) * 100, 2), "%\n")## Độ chính xác trung bình: 83.03 %inspect(sort(good_rules, by = 'confidence'))## lhs rhs support confidence coverage lift count addedValue
## [1] {Banha,
## Donbi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [2] {Banha,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [3] {Agiao,
## Donbi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [4] {Banha,
## Donbi,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [5] {Banha,
## Donbi,
## Ngothudu} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [6] {Banha,
## Donbi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [7] {Banha,
## Donbi,
## Duongquy} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [8] {Banha,
## Ngothudu,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [9] {Banha,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [10] {Banha,
## Duongquy,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [11] {Banha,
## Ngothudu,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [12] {Banha,
## Duongquy,
## Ngothudu} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [13] {Agiao,
## Donbi,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [14] {Agiao,
## Donbi,
## Ngothudu} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [15] {Agiao,
## Donbi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [16] {Agiao,
## Donbi,
## Duongquy} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [17] {Donbi,
## Ngothudu,
## Quechi} => {Machmon} 0.10227273 1 0.10227273 7.333333 9 0.8636364
## [18] {Bachthuoc,
## Donbi,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [19] {Banha,
## Donbi,
## Ngothudu,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [20] {Banha,
## Donbi,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [21] {Banha,
## Donbi,
## Duongquy,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [22] {Banha,
## Donbi,
## Ngothudu,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [23] {Banha,
## Donbi,
## Duongquy,
## Ngothudu} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [24] {Banha,
## Donbi,
## Duongquy,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [25] {Banha,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [26] {Banha,
## Duongquy,
## Ngothudu,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [27] {Banha,
## Duongquy,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [28] {Banha,
## Duongquy,
## Ngothudu,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [29] {Agiao,
## Donbi,
## Ngothudu,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [30] {Agiao,
## Donbi,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [31] {Agiao,
## Donbi,
## Duongquy,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [32] {Agiao,
## Donbi,
## Ngothudu,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [33] {Agiao,
## Donbi,
## Duongquy,
## Ngothudu} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [34] {Agiao,
## Donbi,
## Duongquy,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [35] {Bachthuoc,
## Donbi,
## Ngothudu,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [36] {Donbi,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.10227273 1 0.10227273 7.333333 9 0.8636364
## [37] {Donbi,
## Duongquy,
## Ngothudu,
## Quechi} => {Machmon} 0.10227273 1 0.10227273 7.333333 9 0.8636364
## [38] {Bachthuoc,
## Donbi,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [39] {Bachthuoc,
## Donbi,
## Duongquy,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [40] {Banha,
## Donbi,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [41] {Banha,
## Donbi,
## Duongquy,
## Ngothudu,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [42] {Banha,
## Donbi,
## Duongquy,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [43] {Banha,
## Donbi,
## Duongquy,
## Ngothudu,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [44] {Banha,
## Duongquy,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [45] {Agiao,
## Donbi,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [46] {Agiao,
## Donbi,
## Duongquy,
## Ngothudu,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [47] {Agiao,
## Donbi,
## Duongquy,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [48] {Agiao,
## Donbi,
## Duongquy,
## Ngothudu,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [49] {Bachthuoc,
## Donbi,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [50] {Bachthuoc,
## Donbi,
## Duongquy,
## Ngothudu,
## Quechi} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [51] {Donbi,
## Duongquy,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.10227273 1 0.10227273 7.333333 9 0.8636364
## [52] {Bachthuoc,
## Donbi,
## Duongquy,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [53] {Banha,
## Donbi,
## Duongquy,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [54] {Agiao,
## Donbi,
## Duongquy,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364
## [55] {Bachthuoc,
## Donbi,
## Duongquy,
## Ngothudu,
## Quechi,
## Xuyenkhung} => {Machmon} 0.09090909 1 0.09090909 7.333333 8 0.8636364#Xây dựng quy luật liên kết từng phần
hanngunghuyetu_rules_lhs <- apriori(dat, parameter = list(supp=0.01, conf=0.7, maxlen=10, minlen=2),appearance = list(default="rhs",lhs="Hanngunghuyetu"))## 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
## 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 ...[1 item(s)] done [0.00s].
## set transactions ...[148 item(s), 109 transaction(s)] done [0.00s].
## sorting and recoding items ... [89 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 done [0.00s].
## writing ... [2 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].inspect(sort(hanngunghuyetu_rules_lhs, by = 'confidence')[1:min(20, length(hanngunghuyetu_rules_lhs))])## lhs rhs support confidence coverage lift
## [1] {Hanngunghuyetu} => {Duongquy} 0.3761468 0.8723404 0.4311927 1.044891
## [2] {Hanngunghuyetu} => {Xuyenkhung} 0.3486239 0.8085106 0.4311927 1.087996
## count
## [1] 41
## [2] 38subrules <- head(hanngunghuyetu_rules_lhs , n = 5, by = "confidence")
plot(subrules, shading = "confidence", method = "graph", engine = "htmlwidget")khitrehuyetu_rules_lhs <- apriori(dat, parameter = list(supp=0.01, conf=0.1, maxlen=10, minlen=2),appearance = list(default="rhs",lhs="Khitrehuyetu"))## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.1 0.1 1 none FALSE TRUE 5 0.01 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 ...[1 item(s)] done [0.00s].
## set transactions ...[148 item(s), 109 transaction(s)] done [0.00s].
## sorting and recoding items ... [89 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 done [0.00s].
## writing ... [34 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].subrules1 <- head(khitrehuyetu_rules_lhs, n = 7, by = "confidence")
inspect(sort(khitrehuyetu_rules_lhs , by = 'confidence'))## lhs rhs support confidence coverage lift
## [1] {Khitrehuyetu} => {Duongquy} 0.16513761 0.90 0.1834862 1.0780220
## [2] {Khitrehuyetu} => {Xuyenkhung} 0.13761468 0.75 0.1834862 1.0092593
## [3] {Khitrehuyetu} => {Dienhosach} 0.11926606 0.65 0.1834862 1.1070313
## [4] {Khitrehuyetu} => {Huongphu} 0.11009174 0.60 0.1834862 1.5571429
## [5] {Khitrehuyetu} => {Chixac} 0.09174312 0.50 0.1834862 4.1923077
## [6] {Khitrehuyetu} => {Saiho} 0.08256881 0.45 0.1834862 2.8852941
## [7] {Khitrehuyetu} => {Daonhan} 0.08256881 0.45 0.1834862 2.7250000
## [8] {Khitrehuyetu} => {Xichthuoc} 0.08256881 0.45 0.1834862 1.3256757
## [9] {Khitrehuyetu} => {Honghoa} 0.06422018 0.35 0.1834862 2.5433333
## [10] {Khitrehuyetu} => {Oduoc} 0.06422018 0.35 0.1834862 2.0078947
## [11] {Khitrehuyetu} => {Motduoc} 0.06422018 0.35 0.1834862 1.4673077
## [12] {Khitrehuyetu} => {Nguutat} 0.05504587 0.30 0.1834862 1.4863636
## [13] {Khitrehuyetu} => {Camthao} 0.05504587 0.30 0.1834862 0.8384615
## [14] {Khitrehuyetu} => {Bachthuoc} 0.05504587 0.30 0.1834862 0.5450000
## [15] {Khitrehuyetu} => {Chichthao} 0.04587156 0.25 0.1834862 1.0480769
## [16] {Khitrehuyetu} => {Ngulinhchi} 0.04587156 0.25 0.1834862 0.6987179
## [17] {Khitrehuyetu} => {Uatkim} 0.03669725 0.20 0.1834862 4.3600000
## [18] {Khitrehuyetu} => {Kehuyetdang} 0.03669725 0.20 0.1834862 2.1800000
## [19] {Khitrehuyetu} => {Dansam} 0.03669725 0.20 0.1834862 1.5571429
## [20] {Khitrehuyetu} => {Tieuhoihuong} 0.03669725 0.20 0.1834862 0.7517241
## [21] {Khitrehuyetu} => {Bohoang} 0.03669725 0.20 0.1834862 0.5190476
## [22] {Khitrehuyetu} => {Catcanh} 0.02752294 0.15 0.1834862 4.0875000
## [23] {Khitrehuyetu} => {Thanhbi} 0.02752294 0.15 0.1834862 2.7250000
## [24] {Khitrehuyetu} => {Bachlinh} 0.02752294 0.15 0.1834862 1.3625000
## [25] {Khitrehuyetu} => {Sinhdia} 0.01834862 0.10 0.1834862 3.6333333
## [26] {Khitrehuyetu} => {Trachta} 0.01834862 0.10 0.1834862 1.8166667
## [27] {Khitrehuyetu} => {Tranbi} 0.01834862 0.10 0.1834862 2.1800000
## [28] {Khitrehuyetu} => {Nhuhuong} 0.01834862 0.10 0.1834862 1.8166667
## [29] {Khitrehuyetu} => {Xuyenluyentu} 0.01834862 0.10 0.1834862 1.5571429
## [30] {Khitrehuyetu} => {Mochuong} 0.01834862 0.10 0.1834862 1.2111111
## [31] {Khitrehuyetu} => {Thucdia} 0.01834862 0.10 0.1834862 0.9083333
## [32] {Khitrehuyetu} => {Bachtruat} 0.01834862 0.10 0.1834862 0.7785714
## [33] {Khitrehuyetu} => {Donbi} 0.01834862 0.10 0.1834862 0.6055556
## [34] {Khitrehuyetu} => {Nhucque} 0.01834862 0.10 0.1834862 0.2945946
## count
## [1] 18
## [2] 15
## [3] 13
## [4] 12
## [5] 10
## [6] 9
## [7] 9
## [8] 9
## [9] 7
## [10] 7
## [11] 7
## [12] 6
## [13] 6
## [14] 6
## [15] 5
## [16] 5
## [17] 4
## [18] 4
## [19] 4
## [20] 4
## [21] 4
## [22] 3
## [23] 3
## [24] 3
## [25] 2
## [26] 2
## [27] 2
## [28] 2
## [29] 2
## [30] 2
## [31] 2
## [32] 2
## [33] 2
## [34] 2plot(subrules1, shading = "confidence", method = "graph", engine = "htmlwidget")