library(arules)
library(tidyverse)Assignment3
Import the Retail Transactions
retail_transactions <- read.transactions("retail_transactions_3.csv", sep = ",")Part 2
summary(retail_transactions)transactions as itemMatrix in sparse format with
10000 rows (elements/itemsets/transactions) and
5479 columns (items) and a density of 0.002744552
most frequent items:
WHITE HANGING HEART T-LIGHT HOLDER REGENCY CAKESTAND 3 TIER
822 776
JUMBO BAG RED RETROSPOT PARTY BUNTING
663 561
ASSORTED COLOUR BIRD ORNAMENT (Other)
544 147008
element (itemset/transaction) length distribution:
sizes
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1658 707 498 413 365 341 316 310 309 290 261 227 227 242 260 227
17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
204 199 233 189 184 149 138 125 104 111 112 98 113 99 78 68
33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
55 62 65 44 48 41 52 41 44 26 45 27 27 35 30 24
49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64
26 23 22 21 16 19 21 13 11 16 13 14 15 10 13 13
65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
3 13 13 7 6 9 9 6 6 4 3 8 5 6 3 5
81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96
3 4 5 8 3 5 8 2 4 4 1 3 2 3 1 2
97 98 100 101 102 103 104 105 107 108 109 110 111 112 113 119
5 1 2 2 2 1 2 1 1 3 1 2 1 1 2 1
120 121 122 123 125 127 134 142 146 147 150 154 157 171 193 204
1 1 1 1 1 1 1 2 1 1 1 2 1 2 1 1
235 249
1 1
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.00 3.00 10.00 15.04 21.00 249.00
includes extended item information - examples:
labels
1 1 HANGER
2 10 COLOUR SPACEBOY PEN
3 12 COLOURED PARTY BALLOONSPart 2A
There are 10000 transactions.
5479 = 54,790,000 * 0.002744552 = 150,374 transactions in the dataset.
Part 2B
There are 5479 items available.
## Part 2C
10000 * 5479 = 54,790,000
Part 2C(i)
0.002744552 = 0.2%
54,790,000 * 0.002744552 = 150.374
Part 2D
249
Part 2E
15.04
Part 3
itemFrequencyPlot(retail_transactions, topN = 20, horiz = T)
Part 4
retail_rules <- apriori(retail_transactions, parameter = list (support = 0.01, confidence = 0.5, minlen = 2))Apriori
Parameter specification:
confidence minval smax arem aval originalSupport maxtime support minlen
0.5 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: 100
set item appearances ...[0 item(s)] done [0.00s].
set transactions ...[5479 item(s), 10000 transaction(s)] done [0.06s].
sorting and recoding items ... [384 item(s)] done [0.00s].
creating transaction tree ... done [0.00s].
checking subsets of size 1 2 3 4 done [0.00s].
writing ... [86 rule(s)] done [0.00s].
creating S4 object ... done [0.00s].Part 4A
86 rules are discovered
Part 4B
THE SUPPORT VALUE IS THE PERCENTAGE OF TIMES A PRODUCT WAS PURCHASED TOGETHER IN THE DATA SET, SO FOR THE ALGORITHM IT MEANS THAT IT IS ONLY INCLUDES PRODUCTS THAT HAVE A SUPPORT VALUE OVER 0.01.
Part 4C
THE CONFIDENCE VALUE IS HOW OFTEN ITEMS ARE PURCHASED TOGETHER, SO FOR THIS ALGORITHM IT MEANS THAT THE ITEMS PURCHASED TOGETHER AT LEAST 50% OF THE TIME, A RULE IS CREATED.
Part 5
summary(retail_rules)set of 86 rules
rule length distribution (lhs + rhs):sizes
2 3
47 39
Min. 1st Qu. Median Mean 3rd Qu. Max.
2.000 2.000 2.000 2.453 3.000 3.000
summary of quality measures:
support confidence coverage lift
Min. :0.01000 Min. :0.5021 Min. :0.01200 Min. : 6.585
1st Qu.:0.01063 1st Qu.:0.5510 1st Qu.:0.01733 1st Qu.:12.347
Median :0.01160 Median :0.6022 Median :0.02000 Median :15.266
Mean :0.01315 Mean :0.6198 Mean :0.02152 Mean :17.144
3rd Qu.:0.01515 3rd Qu.:0.6652 3rd Qu.:0.02428 3rd Qu.:21.864
Max. :0.02270 Max. :0.8814 Max. :0.03770 Max. :44.055
count
Min. :100.0
1st Qu.:106.2
Median :116.0
Mean :131.5
3rd Qu.:151.5
Max. :227.0
mining info:
data ntransactions support confidence
retail_transactions 10000 0.01 0.5
call
apriori(data = retail_transactions, parameter = list(support = 0.01, confidence = 0.5, minlen = 2))Part 5A
2 items = 47 rules
3 items = 39 rules
Part 5B
minimum lift value = 6.585
maximum lift value = 44.055
Part 6
inspect(sort(retail_rules, by = "lift")) lhs rhs support confidence coverage lift count
[1] {WOODEN STAR CHRISTMAS SCANDINAVIAN} => {WOODEN HEART CHRISTMAS SCANDINAVIAN} 0.0113 0.7533333 0.0150 44.054581 113
[2] {WOODEN HEART CHRISTMAS SCANDINAVIAN} => {WOODEN STAR CHRISTMAS SCANDINAVIAN} 0.0113 0.6608187 0.0171 44.054581 113
[3] {PINK REGENCY TEACUP AND SAUCER,
ROSES REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.0156 0.8813559 0.0177 28.708662 156
[4] {GREEN REGENCY TEACUP AND SAUCER,
REGENCY CAKESTAND 3 TIER} => {PINK REGENCY TEACUP AND SAUCER} 0.0102 0.6938776 0.0147 28.672626 102
[5] {GREEN REGENCY TEACUP AND SAUCER,
ROSES REGENCY TEACUP AND SAUCER} => {PINK REGENCY TEACUP AND SAUCER} 0.0156 0.6872247 0.0227 28.397714 156
[6] {PINK REGENCY TEACUP AND SAUCER,
REGENCY CAKESTAND 3 TIER} => {GREEN REGENCY TEACUP AND SAUCER} 0.0102 0.8500000 0.0120 27.687296 102
[7] {GARDENERS KNEELING PAD KEEP CALM} => {GARDENERS KNEELING PAD CUP OF TEA} 0.0163 0.5821429 0.0280 26.105061 163
[8] {GARDENERS KNEELING PAD CUP OF TEA} => {GARDENERS KNEELING PAD KEEP CALM} 0.0163 0.7309417 0.0223 26.105061 163
[9] {PINK REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.0192 0.7933884 0.0242 25.843271 192
[10] {GREEN REGENCY TEACUP AND SAUCER} => {PINK REGENCY TEACUP AND SAUCER} 0.0192 0.6254072 0.0307 25.843271 192
[11] {DOLLY GIRL LUNCH BOX} => {SPACEBOY LUNCH BOX} 0.0138 0.6359447 0.0217 25.642931 138
[12] {SPACEBOY LUNCH BOX} => {DOLLY GIRL LUNCH BOX} 0.0138 0.5564516 0.0248 25.642931 138
[13] {GREEN REGENCY TEACUP AND SAUCER,
PINK REGENCY TEACUP AND SAUCER} => {ROSES REGENCY TEACUP AND SAUCER} 0.0156 0.8125000 0.0192 24.399399 156
[14] {REGENCY CAKESTAND 3 TIER,
ROSES REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.0116 0.7483871 0.0155 24.377430 116
[15] {JUMBO BAG PEARS} => {JUMBO BAG APPLES} 0.0111 0.6529412 0.0170 24.272906 111
[16] {GREEN REGENCY TEACUP AND SAUCER,
REGENCY CAKESTAND 3 TIER} => {ROSES REGENCY TEACUP AND SAUCER} 0.0116 0.7891156 0.0147 23.697167 116
[17] {GREEN REGENCY TEACUP AND SAUCER} => {ROSES REGENCY TEACUP AND SAUCER} 0.0227 0.7394137 0.0307 22.204615 227
[18] {ROSES REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.0227 0.6816817 0.0333 22.204615 227
[19] {ROUND SNACK BOXES SET OF 4 FRUITS} => {ROUND SNACK BOXES SET OF4 WOODLAND} 0.0100 0.5524862 0.0181 22.188200 100
[20] {PINK REGENCY TEACUP AND SAUCER} => {ROSES REGENCY TEACUP AND SAUCER} 0.0177 0.7314050 0.0242 21.964113 177
[21] {ROSES REGENCY TEACUP AND SAUCER} => {PINK REGENCY TEACUP AND SAUCER} 0.0177 0.5315315 0.0333 21.964113 177
[22] {ALARM CLOCK BAKELIKE GREEN,
ALARM CLOCK BAKELIKE PINK} => {ALARM CLOCK BAKELIKE RED} 0.0100 0.7575758 0.0132 21.895253 100
[23] {LARGE WHITE HEART OF WICKER} => {SMALL WHITE HEART OF WICKER} 0.0113 0.5159817 0.0219 21.771381 113
[24] {ALARM CLOCK BAKELIKE PINK,
ALARM CLOCK BAKELIKE RED} => {ALARM CLOCK BAKELIKE GREEN} 0.0100 0.6666667 0.0150 21.299255 100
[25] {CHARLOTTE BAG PINK POLKADOT} => {RED RETROSPOT CHARLOTTE BAG} 0.0127 0.6256158 0.0203 20.923604 127
[26] {HOT WATER BOTTLE I AM SO POORLY} => {CHOCOLATE HOT WATER BOTTLE} 0.0102 0.5454545 0.0187 20.661157 102
[27] {STRAWBERRY CHARLOTTE BAG} => {RED RETROSPOT CHARLOTTE BAG} 0.0117 0.6157895 0.0190 20.594966 117
[28] {ALARM CLOCK BAKELIKE GREEN,
ALARM CLOCK BAKELIKE RED} => {ALARM CLOCK BAKELIKE PINK} 0.0100 0.5025126 0.0199 20.344638 100
[29] {ALARM CLOCK BAKELIKE IVORY} => {ALARM CLOCK BAKELIKE RED} 0.0120 0.6896552 0.0174 19.932230 120
[30] {BAKING SET SPACEBOY DESIGN} => {BAKING SET 9 PIECE RETROSPOT} 0.0115 0.6388889 0.0180 19.597819 115
[31] {ALARM CLOCK BAKELIKE GREEN} => {ALARM CLOCK BAKELIKE RED} 0.0199 0.6357827 0.0313 18.375224 199
[32] {ALARM CLOCK BAKELIKE RED} => {ALARM CLOCK BAKELIKE GREEN} 0.0199 0.5751445 0.0346 18.375224 199
[33] {LUNCH BAG CARS BLUE,
LUNCH BAG RED RETROSPOT} => {LUNCH BAG WOODLAND} 0.0101 0.5343915 0.0189 17.578669 101
[34] {ALARM CLOCK BAKELIKE PINK} => {ALARM CLOCK BAKELIKE RED} 0.0150 0.6072874 0.0247 17.551660 150
[35] {CHARLOTTE BAG SUKI DESIGN} => {RED RETROSPOT CHARLOTTE BAG} 0.0114 0.5181818 0.0220 17.330496 114
[36] {WOODLAND CHARLOTTE BAG} => {RED RETROSPOT CHARLOTTE BAG} 0.0111 0.5115207 0.0217 17.107717 111
[37] {ALARM CLOCK BAKELIKE PINK} => {ALARM CLOCK BAKELIKE GREEN} 0.0132 0.5344130 0.0247 17.073896 132
[38] {WOODEN PICTURE FRAME WHITE FINISH} => {WOODEN FRAME ANTIQUE WHITE} 0.0197 0.5487465 0.0359 16.283279 197
[39] {WOODEN FRAME ANTIQUE WHITE} => {WOODEN PICTURE FRAME WHITE FINISH} 0.0197 0.5845697 0.0337 16.283279 197
[40] {LUNCH BAG CARS BLUE,
LUNCH BAG RED RETROSPOT} => {LUNCH BAG PINK POLKADOT} 0.0116 0.6137566 0.0189 16.280016 116
[41] {LUNCH BAG BLACK SKULL,
LUNCH BAG CARS BLUE} => {LUNCH BAG PINK POLKADOT} 0.0108 0.6000000 0.0180 15.915119 108
[42] {LUNCH BAG RED RETROSPOT,
LUNCH BAG SUKI DESIGN} => {LUNCH BAG PINK POLKADOT} 0.0103 0.5953757 0.0173 15.792459 103
[43] {LUNCH BAG RED RETROSPOT,
LUNCH BAG WOODLAND} => {LUNCH BAG CARS BLUE} 0.0101 0.5906433 0.0171 15.301639 101
[44] {LUNCH BAG BLACK SKULL,
LUNCH BAG RED RETROSPOT} => {LUNCH BAG PINK POLKADOT} 0.0120 0.5741627 0.0209 15.229779 120
[45] {LUNCH BAG DOLLY GIRL DESIGN} => {LUNCH BAG SPACEBOY DESIGN} 0.0131 0.5796460 0.0226 15.213806 131
[46] {LUNCH BAG BLACK SKULL,
LUNCH BAG PINK POLKADOT} => {LUNCH BAG CARS BLUE} 0.0108 0.5775401 0.0187 14.962179 108
[47] {LUNCH BAG CARS BLUE,
LUNCH BAG RED RETROSPOT} => {LUNCH BAG BLACK SKULL} 0.0118 0.6243386 0.0189 14.829896 118
[48] {LUNCH BAG RED RETROSPOT,
LUNCH BAG SPACEBOY DESIGN} => {LUNCH BAG PINK POLKADOT} 0.0101 0.5580110 0.0181 14.801354 101
[49] {LUNCH BAG PINK POLKADOT,
LUNCH BAG RED RETROSPOT} => {LUNCH BAG CARS BLUE} 0.0116 0.5686275 0.0204 14.731281 116
[50] {LUNCH BAG BLACK SKULL,
LUNCH BAG RED RETROSPOT} => {LUNCH BAG CARS BLUE} 0.0118 0.5645933 0.0209 14.626769 118
[51] {LUNCH BAG CARS BLUE,
LUNCH BAG PINK POLKADOT} => {LUNCH BAG BLACK SKULL} 0.0108 0.6101695 0.0177 14.493337 108
[52] {LUNCH BAG VINTAGE LEAF DESIGN} => {LUNCH BAG APPLE DESIGN} 0.0122 0.5020576 0.0243 14.468519 122
[53] {LUNCH BAG RED RETROSPOT,
LUNCH BAG WOODLAND} => {LUNCH BAG BLACK SKULL} 0.0102 0.5964912 0.0171 14.168438 102
[54] {LUNCH BAG PINK POLKADOT,
LUNCH BAG RED RETROSPOT} => {LUNCH BAG SUKI DESIGN} 0.0103 0.5049020 0.0204 14.064121 103
[55] {LUNCH BAG RED RETROSPOT,
LUNCH BAG SPACEBOY DESIGN} => {LUNCH BAG BLACK SKULL} 0.0107 0.5911602 0.0181 14.041810 107
[56] {LUNCH BAG RED RETROSPOT,
LUNCH BAG SUKI DESIGN} => {LUNCH BAG BLACK SKULL} 0.0102 0.5895954 0.0173 14.004641 102
[57] {LUNCH BAG PINK POLKADOT,
LUNCH BAG RED RETROSPOT} => {LUNCH BAG BLACK SKULL} 0.0120 0.5882353 0.0204 13.972335 120
[58] {LUNCH BAG CARS BLUE,
LUNCH BAG WOODLAND} => {LUNCH BAG RED RETROSPOT} 0.0101 0.7266187 0.0139 13.735703 101
[59] {LUNCH BAG BLACK SKULL,
LUNCH BAG WOODLAND} => {LUNCH BAG RED RETROSPOT} 0.0102 0.7183099 0.0142 13.578636 102
[60] {LUNCH BAG BLACK SKULL,
LUNCH BAG RED RETROSPOT} => {LUNCH BAG SPACEBOY DESIGN} 0.0107 0.5119617 0.0209 13.437316 107
[61] {LUNCH BAG PINK POLKADOT,
LUNCH BAG SPACEBOY DESIGN} => {LUNCH BAG RED RETROSPOT} 0.0101 0.7013889 0.0144 13.258769 101
[62] {PAINTED METAL PEARS ASSORTED} => {ASSORTED COLOUR BIRD ORNAMENT} 0.0106 0.7210884 0.0147 13.255302 106
[63] {LUNCH BAG BLACK SKULL,
LUNCH BAG CARS BLUE} => {LUNCH BAG RED RETROSPOT} 0.0118 0.6555556 0.0180 12.392355 118
[64] {LUNCH BAG CARS BLUE,
LUNCH BAG PINK POLKADOT} => {LUNCH BAG RED RETROSPOT} 0.0116 0.6553672 0.0177 12.388795 116
[65] {LUNCH BAG BLACK SKULL,
LUNCH BAG SPACEBOY DESIGN} => {LUNCH BAG RED RETROSPOT} 0.0107 0.6524390 0.0164 12.333441 107
[66] {LUNCH BAG PINK POLKADOT,
LUNCH BAG SUKI DESIGN} => {LUNCH BAG RED RETROSPOT} 0.0103 0.6518987 0.0158 12.323227 103
[67] {60 TEATIME FAIRY CAKE CASES} => {PACK OF 72 RETROSPOT CAKE CASES} 0.0134 0.5056604 0.0265 12.184587 134
[68] {LUNCH BAG BLACK SKULL,
LUNCH BAG PINK POLKADOT} => {LUNCH BAG RED RETROSPOT} 0.0120 0.6417112 0.0187 12.130647 120
[69] {LUNCH BAG BLACK SKULL,
LUNCH BAG SUKI DESIGN} => {LUNCH BAG RED RETROSPOT} 0.0102 0.6144578 0.0166 11.615460 102
[70] {LUNCH BAG WOODLAND} => {LUNCH BAG RED RETROSPOT} 0.0171 0.5625000 0.0304 10.633270 171
[71] {LUNCH BAG PINK POLKADOT} => {LUNCH BAG RED RETROSPOT} 0.0204 0.5411141 0.0377 10.228999 204
[72] {LUNCH BAG DOLLY GIRL DESIGN} => {LUNCH BAG RED RETROSPOT} 0.0121 0.5353982 0.0226 10.120950 121
[73] {JUMBO BAG STRAWBERRY} => {JUMBO BAG RED RETROSPOT} 0.0172 0.6515152 0.0264 9.826775 172
[74] {JUMBO BAG SCANDINAVIAN BLUE PAISLEY} => {JUMBO BAG RED RETROSPOT} 0.0108 0.6352941 0.0170 9.582113 108
[75] {JUMBO BAG PINK POLKADOT} => {JUMBO BAG RED RETROSPOT} 0.0223 0.6043360 0.0369 9.115174 223
[76] {CANDLEHOLDER PINK HANGING HEART} => {WHITE HANGING HEART T-LIGHT HOLDER} 0.0111 0.7449664 0.0149 9.062852 111
[77] {JUMBO BAG SPACEBOY DESIGN} => {JUMBO BAG RED RETROSPOT} 0.0113 0.5978836 0.0189 9.017852 113
[78] {JUMBO STORAGE BAG SUKI} => {JUMBO BAG RED RETROSPOT} 0.0186 0.5904762 0.0315 8.906127 186
[79] {RED HANGING HEART T-LIGHT HOLDER} => {WHITE HANGING HEART T-LIGHT HOLDER} 0.0186 0.6888889 0.0270 8.380643 186
[80] {JUMBO BAG BAROQUE BLACK WHITE} => {JUMBO BAG RED RETROSPOT} 0.0147 0.5505618 0.0267 8.304100 147
[81] {JUMBO BAG PINK VINTAGE PAISLEY} => {JUMBO BAG RED RETROSPOT} 0.0128 0.5493562 0.0233 8.285916 128
[82] {JUMBO BAG VINTAGE DOILY} => {JUMBO BAG RED RETROSPOT} 0.0116 0.5155556 0.0225 7.776102 116
[83] {JUMBO SHOPPER VINTAGE RED PAISLEY} => {JUMBO BAG RED RETROSPOT} 0.0152 0.5033113 0.0302 7.591422 152
[84] {JUMBO BAG WOODLAND ANIMALS} => {JUMBO BAG RED RETROSPOT} 0.0101 0.5024876 0.0201 7.578998 101
[85] {GREEN REGENCY TEACUP AND SAUCER,
PINK REGENCY TEACUP AND SAUCER} => {REGENCY CAKESTAND 3 TIER} 0.0102 0.5312500 0.0192 6.846005 102
[86] {GREEN REGENCY TEACUP AND SAUCER,
ROSES REGENCY TEACUP AND SAUCER} => {REGENCY CAKESTAND 3 TIER} 0.0116 0.5110132 0.0227 6.585222 116Part 6A(i)
If they bought WOODEN STAR CHRISTMAS SCANDINAVIAN it is implied that they will buy WOODEN HEART CHRISTMAS SCANDINAVIAN
Part 6A(ii)
confidence = 0.7533333 which means it is correct 75% of the time for purchases involving WOODEN STAR CHRISTMAS SCANDINAVIAN.
support = 0.0113 which means it covers 1.13% of all purchases.
Part 6A(iii)
Transactions including WOODEN STAR CHRISTMAS SCANDINAVIAN makes it 44.054581 more likely they will also buy WOODEN HEART CHRISTMAS SCANDINAVIAN
Part 6(b)
Trivial – rules that are so obvious that they are not worth mentioning. Example - wooden star christmas scandinavian and wooden heart christmas scandinavian.Part 6 (c)
Actional rules provide insights that we can take action on to improve sales. Emample - PINK REGENCY TEACUP AND SAUCER and ROSES REGENCY TEACUP AND SAUCER. Management could do a 2 for 1 or buy 1 get 50% off the other deals to encourage second item purchase.
Part 7
rosesregancyteacupandsaucer_rules <- subset(retail_rules, items %in% "ROSES REGENCY TEACUP AND SAUCER")
inspect(rosesregancyteacupandsaucer_rules) lhs rhs support confidence coverage lift count
[1] {PINK REGENCY TEACUP AND SAUCER} => {ROSES REGENCY TEACUP AND SAUCER} 0.0177 0.7314050 0.0242 21.964113 177
[2] {ROSES REGENCY TEACUP AND SAUCER} => {PINK REGENCY TEACUP AND SAUCER} 0.0177 0.5315315 0.0333 21.964113 177
[3] {GREEN REGENCY TEACUP AND SAUCER} => {ROSES REGENCY TEACUP AND SAUCER} 0.0227 0.7394137 0.0307 22.204615 227
[4] {ROSES REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.0227 0.6816817 0.0333 22.204615 227
[5] {GREEN REGENCY TEACUP AND SAUCER,
PINK REGENCY TEACUP AND SAUCER} => {ROSES REGENCY TEACUP AND SAUCER} 0.0156 0.8125000 0.0192 24.399399 156
[6] {PINK REGENCY TEACUP AND SAUCER,
ROSES REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.0156 0.8813559 0.0177 28.708662 156
[7] {GREEN REGENCY TEACUP AND SAUCER,
ROSES REGENCY TEACUP AND SAUCER} => {PINK REGENCY TEACUP AND SAUCER} 0.0156 0.6872247 0.0227 28.397714 156
[8] {GREEN REGENCY TEACUP AND SAUCER,
ROSES REGENCY TEACUP AND SAUCER} => {REGENCY CAKESTAND 3 TIER} 0.0116 0.5110132 0.0227 6.585222 116
[9] {GREEN REGENCY TEACUP AND SAUCER,
REGENCY CAKESTAND 3 TIER} => {ROSES REGENCY TEACUP AND SAUCER} 0.0116 0.7891156 0.0147 23.697167 116
[10] {REGENCY CAKESTAND 3 TIER,
ROSES REGENCY TEACUP AND SAUCER} => {GREEN REGENCY TEACUP AND SAUCER} 0.0116 0.7483871 0.0155 24.377430 116Question 2
Part 1
library(recommenderlab)
library(tidyverse)Part 2
steam_ratings <- read_csv("steam_ratings.csv")
steam_ratings <- as(steam_ratings, "matrix")
steam_ratings <- as(steam_ratings, "realRatingMatrix")Part 3(a)
data(steam_ratings)
steam_ratings2080 x 1581 rating matrix of class 'realRatingMatrix' with 52414 ratings.View(as(MovieLense, “matrix”))
View(as(steam_ratings, "matrix"))vector_ratings <- as.vector(steam_ratings@data)
table(vector_ratings)vector_ratings
0 1 2 3 4 5
3236066 4773 12500 19762 10655 4724 Part 3(b)
colMeans(steam_ratings) %>%
tibble::enframe(name = "games", value = "vector_rating") %>%
ggplot() +
geom_histogram(mapping = aes(x = vector_rating), color = "magenta", fill = "magenta4", bins = 30) +
labs(
title = "Distribution of Average Game Ratings",
x = "Average Rating",
y = "Count",
caption = "Data source: Steam Ratings"
) +
theme_minimal()
Part 3(c)
user_game_counts <- rowCounts(steam_ratings)
user_game_counts %>%
tibble::enframe(name = "user", value = "num_games_rated") %>%
ggplot() +
geom_histogram(mapping = aes(x = num_games_rated), color = "magenta", fill = "magenta4", bins = 30) +
labs(
title = "Distribution of Total Games Rated by Each User",
x = "Number of Games Rated",
y = "Count of Users",
caption = "Data source: Steam Ratings"
) +
theme_minimal()
Part 4(a)
set.seed(101)Part 4(b)
eval_games <- evaluationScheme(data = steam_ratings,
method = "split",
train = 0.8,
given = 6,
goodRating = 3)Part 4(c)
train_games <- getData (eval_games, "train")
known_games <- getData (eval_games, "known")
unknown_games <- getData (eval_games, "unknown")Part 5(a)
ubcf_model_1 <- Recommender(data = train_games,
method = "UBCF",
parameter = list(normalize = "center", method = "Cosine"))
ubcf_model_2 <- Recommender(data = train_games,
method = "UBCF",
parameter = list(normalize = "Z-score", method = "Cosine"))
ubcf_model_3 <- Recommender(data = train_games,
method = "UBCF",
parameter = list(normalize = NULL, method = "Cosine"))
ubcf_model_4 <- Recommender(data = train_games,
method = "UBCF",
parameter = list(normalize = "center", method = "Euclidean"))
ubcf_model_5 <- Recommender(data = train_games,
method = "UBCF",
parameter = list(normalize = "Z-score", method = "Euclidean"))
ubcf_model_6 <- Recommender(data = train_games,
method = "UBCF",
parameter = list(normalize = NULL, method = "Euclidean"))
ubcf_model_7 <- Recommender(data = train_games,
method = "UBCF",
parameter = list(normalize = "center", method = "Pearson"))
ubcf_model_8 <- Recommender(data = train_games,
method = "UBCF",
parameter = list(normalize = "Z-score", method = "Pearson"))
ubcf_model_9 <- Recommender(data = train_games,
method = "UBCF",
parameter = list(normalize = NULL, method = "Pearson"))Part 5 (b)
ubcf_predict_1 <- predict(object = ubcf_model_1,
newdata = known_games,
type = "ratings")
ubcf_eval_1 <- calcPredictionAccuracy(x = ubcf_predict_1,
data = unknown_games)
ubcf_eval_1 RMSE MSE MAE
1.1697655 1.3683514 0.9183398 MAE = 0.9183398ubcf_predict_2 <- predict(object = ubcf_model_2,
newdata = known_games,
type = "ratings")
ubcf_eval_2 <- calcPredictionAccuracy(x = ubcf_predict_2,
data = unknown_games)
ubcf_eval_2 RMSE MSE MAE
1.184555 1.403170 0.923375 MAE = 0.923375ubcf_predict_3 <- predict(object = ubcf_model_3,
newdata = known_games,
type = "ratings")
ubcf_eval_3 <- calcPredictionAccuracy(x = ubcf_predict_3,
data = unknown_games)
ubcf_eval_3 RMSE MSE MAE
1.0793268 1.1649463 0.8189319 MAE = 0.8189319ubcf_predict_4 <- predict(object = ubcf_model_4,
newdata = known_games,
type = "ratings")
ubcf_eval_4 <- calcPredictionAccuracy(x = ubcf_predict_4,
data = unknown_games)
ubcf_eval_4 RMSE MSE MAE
1.1910345 1.4185633 0.9163087 MAE = 0.9163087ubcf_predict_5 <- predict(object = ubcf_model_5,
newdata = known_games,
type = "ratings")
ubcf_eval_5 <- calcPredictionAccuracy(x = ubcf_predict_5,
data = unknown_games)
ubcf_eval_5 RMSE MSE MAE
1.2103032 1.4648339 0.9309624 MAE = 0.9309624ubcf_predict_6 <- predict(object = ubcf_model_6,
newdata = known_games,
type = "ratings")
ubcf_eval_6 <- calcPredictionAccuracy(x = ubcf_predict_6,
data = unknown_games)
ubcf_eval_6 RMSE MSE MAE
1.0990975 1.2080152 0.8294308 MAE = 0.8294308ubcf_predict_7 <- predict(object = ubcf_model_7,
newdata = known_games,
type = "ratings")
ubcf_eval_7 <- calcPredictionAccuracy(x = ubcf_predict_7,
data = unknown_games)
ubcf_eval_7 RMSE MSE MAE
1.1212624 1.2572293 0.8702777 MAE = 0.8702777ubcf_predict_8 <- predict(object = ubcf_model_8,
newdata = known_games,
type = "ratings")
ubcf_eval_8 <- calcPredictionAccuracy(x = ubcf_predict_8,
data = unknown_games)
ubcf_eval_8 RMSE MSE MAE
1.1345807 1.2872733 0.8790968 MAE = 0.8790968ubcf_predict_9 <- predict(object = ubcf_model_9,
newdata = known_games,
type = "ratings")
ubcf_eval_9 <- calcPredictionAccuracy(x = ubcf_predict_9,
data = unknown_games)
ubcf_eval_9 RMSE MSE MAE
1.1086429 1.2290892 0.8349371 MAE = 0.8349371Part 6(a)
ibcf_model_1 <- Recommender(data = train_games,
method = "IBCF",
parameter = list(normalize = "center", method = "Cosine"))
ibcf_model_2 <- Recommender(data = train_games,
method = "IBCF",
parameter = list(normalize = "Z-score", method = "Cosine"))
ibcf_model_3 <- Recommender(data = train_games,
method = "IBCF",
parameter = list(normalize = NULL, method = "Cosine"))
ibcf_model_4 <- Recommender(data = train_games,
method = "IBCF",
parameter = list(normalize = "center", method = "Euclidean"))
ibcf_model_5 <- Recommender(data = train_games,
method = "IBCF",
parameter = list(normalize = "Z-score", method = "Euclidean"))
ibcf_model_6 <- Recommender(data = train_games,
method = "IBCF",
parameter = list(normalize = NULL, method = "Euclidean"))
ibcf_model_7 <- Recommender(data = train_games,
method = "IBCF",
parameter = list(normalize = "center", method = "Pearson"))
ibcf_model_8 <- Recommender(data = train_games,
method = "IBCF",
parameter = list(normalize = "Z-score", method = "Pearson"))
ibcf_model_9 <- Recommender(data = train_games,
method = "IBCF",
parameter = list(normalize = NULL, method = "Pearson"))Part 6(b)
ibcf_predict_1 <- predict(object = ibcf_model_1,
newdata = known_games,
type = "ratings")
ibcf_eval <- calcPredictionAccuracy(x = ibcf_predict_1,
data = unknown_games)
ibcf_eval RMSE MSE MAE
1.500713 2.252139 1.165198 MAE = 1.165198ibcf_predict_2 <- predict(object = ibcf_model_2,
newdata = known_games,
type = "ratings")
ibcf_eval <- calcPredictionAccuracy(x = ibcf_predict_2,
data = unknown_games)
ibcf_eval RMSE MSE MAE
1.500976 2.252928 1.163775 MAE = 1.163775ibcf_predict_3 <- predict(object = ibcf_model_3,
newdata = known_games,
type = "ratings")
ibcf_eval <- calcPredictionAccuracy(x = ibcf_predict_3,
data = unknown_games)
ibcf_eval RMSE MSE MAE
1.587257 2.519385 1.239649 MAE = 1.239649ibcf_predict_4 <- predict(object = ibcf_model_4,
newdata = known_games,
type = "ratings")
ibcf_eval <- calcPredictionAccuracy(x = ibcf_predict_4,
data = unknown_games)
ibcf_eval RMSE MSE MAE
1.477274 2.182339 1.142542 MAE = 1.142542ibcf_predict_5 <- predict(object = ibcf_model_5,
newdata = known_games,
type = "ratings")
ibcf_eval <- calcPredictionAccuracy(x = ibcf_predict_5,
data = unknown_games)
ibcf_eval RMSE MSE MAE
1.475157 2.176087 1.141132 MAE = 1.141132ibcf_predict_6 <- predict(object = ibcf_model_6,
newdata = known_games,
type = "ratings")
ibcf_eval <- calcPredictionAccuracy(x = ibcf_predict_6,
data = unknown_games)
ibcf_eval RMSE MSE MAE
1.476175 2.179092 1.140654 MAE = 1.140654ibcf_predict_7 <- predict(object = ibcf_model_7,
newdata = known_games,
type = "ratings")
ibcf_eval <- calcPredictionAccuracy(x = ibcf_predict_7,
data = unknown_games)
ibcf_eval RMSE MSE MAE
1.470169 2.161397 1.158908 MAE = 1.158908ibcf_predict_8 <- predict(object = ibcf_model_8,
newdata = known_games,
type = "ratings")
ibcf_eval <- calcPredictionAccuracy(x = ibcf_predict_8,
data = unknown_games)
ibcf_eval RMSE MSE MAE
1.467355 2.153130 1.158796 MAE = 1.156796ibcf_predict_9 <- predict(object = ibcf_model_9,
newdata = known_games,
type = "ratings")
ibcf_eval <- calcPredictionAccuracy(x = ibcf_predict_9,
data = unknown_games)
ibcf_eval RMSE MSE MAE
1.456788 2.122230 1.152312 MAE = 1.152312Part 7
ubcf_recs <- predict (object = ubcf_model_3,
newdata = known_games,
type = "ratings",
n = 3)
ubcf_recs_list <- as(ubcf_recs, "list")
ubcf_recs_list[1:5]$`0`
AdVenture Capitalist
2.500000
Age of Empires II HD Edition
2.000000
AirMech
2.000000
Alien Isolation
4.000000
Amazing World
4.000000
Amnesia The Dark Descent
3.500000
Anno 1404
3.000000
Archeblade
3.000000
ARK Survival Evolved
3.000000
Arma 2
2.000000
Arma 3
3.000000
Arma Cold War Assault
3.000000
Aura Kingdom
3.000000
Banished
4.000000
Battle Nations
1.000000
BioShock 2
4.000000
Blacklight Retribution
2.500000
Borderlands
2.000000
Borderlands 2
3.200000
Bridge Constructor
5.000000
Burnout Paradise The Ultimate Box
3.000000
Call of Duty Black Ops
3.000000
Call of Duty Black Ops II
3.000000
Call of Duty Black Ops II - Zombies
2.000000
Call of Duty Ghosts
4.000000
Call of Duty Modern Warfare 3
3.500000
Call of Duty Modern Warfare 3 - Multiplayer
3.000000
Call of Duty World at War
4.000000
Canyon Capers
4.000000
Car Mechanic Simulator 2014
5.000000
Castle Crashers
4.000000
Champions Online
3.000000
Cities Skylines
4.000000
Codename CURE
1.000000
Counter-Strike Global Offensive
2.750000
Counter-Strike Nexon Zombies
2.000000
Counter-Strike Source
3.000000
Crash Time II
3.000000
Creativerse
4.000000
Cry of Fear
4.000000
Crysis
4.000000
Crysis 2 Maximum Edition
4.000000
Darksiders
2.000000
Darksiders II
4.000000
Day of Defeat Source
2.000000
DayZ
2.000000
DC Universe Online
2.333333
Dead Island
3.000000
Dead Realm
3.000000
Defiance
1.000000
Democracy 3
5.000000
Dino D-Day
1.000000
Dirty Bomb
2.000000
Don't Starve Together Beta
2.000000
Dota 2
2.200000
Driver San Francisco
3.000000
Dungeon Defenders II
4.000000
Echo of Soul
4.000000
Endless Sky
3.500000
Epigenesis
1.000000
Euro Truck Simulator 2
4.000000
Everlasting Summer
2.000000
EVGA PrecisionX 16
1.000000
F.E.A.R. 3
4.000000
Fallen Earth
2.000000
Fallout 4
4.000000
Fallout New Vegas
3.500000
Far Cry 3
3.000000
Farming Simulator 15
4.000000
Farming Simulator 2013
2.000000
FlatOut Ultimate Carnage
4.000000
Football Manager 2009
4.000000
Football Manager 2010
4.000000
Football Manager 2011
4.000000
Football Manager 2012
4.000000
Football Manager 2013
3.000000
Football Manager 2014
3.000000
Football Manager 2015
3.000000
Frozen Hearth
5.000000
Game of Thrones - A Telltale Games Series
4.000000
GameMaker Studio
2.000000
Garry's Mod
2.333333
Gauntlet
3.000000
Grand Theft Auto IV
3.000000
Grand Theft Auto San Andreas
3.000000
Half-Life
3.000000
Half-Life 2 Deathmatch
3.000000
Half-Life 2 Episode One
4.000000
Half-Life 2 Episode Two
5.000000
Half-Life 2 Lost Coast
3.000000
Half-Life 2 Update
5.000000
Half-Life Blue Shift
4.000000
Half-Life Opposing Force
4.000000
HAWKEN
2.000000
Hazard Ops
3.000000
Heroes & Generals
2.500000
I am Bread
4.000000
Infinite Crisis
1.000000
Just Cause 2
1.000000
Just Cause 2 Multiplayer Mod
2.000000
Keep Talking and Nobody Explodes
5.000000
Kingdoms of Amalur Reckoning
3.000000
L.A. Noire
4.000000
La Tale
4.000000
Left 4 Dead 2
2.000000
Loadout
1.000000
Mafia II
3.500000
Magic 2014
3.000000
Magic Duels
2.000000
Magicka
4.000000
Magicka Wizard Wars
2.000000
McPixel
4.000000
MechWarrior Online
2.000000
Metro 2033
3.000000
Metro Conflict
1.000000
Metro Last Light
4.000000
Microsoft Flight Simulator X Steam Edition
3.000000
Mirror's Edge
2.000000
Natural Selection 2
2.000000
Need for Speed Hot Pursuit
3.000000
Need for Speed SHIFT
3.000000
NEOTOKYO
3.000000
Neverwinter
2.000000
No More Room in Hell
3.000000
Nosgoth
2.750000
Ori and the Blind Forest
3.000000
Outlast
3.000000
PAC-MAN Championship Edition DX+
3.000000
Path of Exile
3.000000
PAYDAY The Heist
2.000000
Pid
4.000000
Pinball FX2
3.000000
Plague Inc Evolved
4.000000
PlanetSide 2
2.000000
Plants vs. Zombies Game of the Year
4.000000
Portal
3.500000
Portal 2
3.000000
Portal Stories Mel
5.000000
Prison Architect
3.000000
Quake Live
3.000000
RACE 07
4.000000
RaceRoom Racing Experience
3.000000
Ragnarok
3.000000
Ragnarok Online 2
3.000000
Realm of the Mad God
3.000000
Retro City Rampage DX
3.000000
RIFT
2.000000
Robocraft
1.500000
Saints Row 2
2.000000
Saints Row IV
4.000000
Saints Row The Third
3.000000
Sanctum 2
3.000000
Screencheat
4.000000
Sid Meier's Civilization V
3.000000
SimCity 4 Deluxe
3.000000
Sniper Elite V2
2.000000
Soldier Front 2
4.000000
Sonic Adventure 2
5.000000
Source Filmmaker
1.000000
Space Engineers
1.000000
Space Run
5.000000
Starbound
2.000000
State of Decay
1.000000
Stranded Deep
5.000000
Stronghold Kingdoms
1.000000
Surgeon Simulator
3.000000
Survarium
2.000000
System Shock 2
1.000000
Tactical Intervention
2.000000
Team Fortress 2
1.733333
Terraria
2.750000
The Darkness II
5.000000
The Sims(TM) 3
4.000000
The Stanley Parable
4.000000
The Talos Principle
2.000000
Time Clickers
5.000000
Tom Clancy's Ghost Recon Phantoms - EU
3.000000
Tom Clancy's Ghost Recon Phantoms - NA
2.000000
Torchlight II
3.000000
Toribash
3.000000
Total War Battles KINGDOM
3.000000
Train Fever
5.000000
Trainz Simulator 12
4.000000
Tropico 5
4.000000
Trove
2.000000
Unturned
2.375000
War Thunder
2.000000
Warface
3.000000
Warframe
2.000000
World of Goo
3.000000
X-COM UFO Defense
5.000000
You Have to Win the Game
1.000000
$`1`
7 Days to Die
2.500000
8BitMMO
5.000000
AdVenture Capitalist
2.250000
Age of Chivalry
2.000000
Age of Empires II HD Edition
2.750000
Age of Empires III Complete Collection
2.000000
Age of Wonders III
3.000000
Airline Tycoon 2
5.000000
AirMech
2.000000
Alan Wake's American Nightmare
5.000000
Alien Isolation
3.500000
Alien Swarm
3.000000
Aliens vs. Predator
3.000000
Amnesia A Machine for Pigs
3.000000
Amnesia The Dark Descent
4.000000
Archeblade
4.000000
ARK Survival Evolved
2.000000
Arma 2
3.500000
Arma 2 DayZ Mod
3.000000
Arma 2 Operation Arrowhead
3.500000
Arma 3
2.000000
Arma Cold War Assault
3.000000
Assassin's Creed III
3.000000
Assassin's Creed IV Black Flag
4.000000
Assetto Corsa
3.000000
Audiosurf
4.000000
Baldur's Gate Enhanced Edition
2.000000
Banished
3.400000
Bastion
5.000000
Batman Arkham Asylum GOTY Edition
3.500000
Batman Arkham City
4.500000
Batman Arkham City GOTY
3.000000
Battle Nations
1.000000
BattleBlock Theater
5.000000
Battlefield 2
3.000000
Beat Hazard
3.000000
Besiege
3.000000
BioShock
4.000000
BioShock Infinite
2.333333
Blacklight Retribution
4.000000
Blockland
4.000000
Blockstorm
4.000000
Blood Bowl Chaos Edition
2.000000
Borderlands
3.000000
Borderlands 2
2.857143
Borderlands 2 RU
1.500000
Brawlhalla
3.000000
Brick-Force
3.000000
Bridge Constructor
5.000000
Burnout Paradise The Ultimate Box
3.000000
Call of Duty Black Ops
3.500000
Call of Duty Black Ops - Multiplayer
3.500000
Call of Duty Black Ops II
2.000000
Call of Duty Black Ops II - Multiplayer
1.500000
Call of Duty Black Ops II - Zombies
3.000000
Call of Duty Modern Warfare 2
3.500000
Call of Duty Modern Warfare 2 - Multiplayer
3.500000
Call of Duty Modern Warfare 3
3.500000
Call of Duty Modern Warfare 3 - Multiplayer
2.500000
Call of Duty World at War
4.000000
Call of Juarez Gunslinger
4.000000
Car Mechanic Simulator 2014
5.000000
Castle Crashers
4.000000
Champions Online
5.000000
Chivalry Medieval Warfare
2.000000
Cities Skylines
5.000000
Clicker Heroes
2.000000
Command and Conquer 3 Kane's Wrath
5.000000
Command and Conquer 3 Tiberium Wars
3.000000
Command and Conquer 4 Tiberian Twilight
3.000000
Company of Heroes
3.000000
Company of Heroes 2
3.000000
Company of Heroes Opposing Fronts
1.000000
Construction-Simulator 2015
3.000000
Contagion
3.000000
Cook, Serve, Delicious!
5.000000
Counter-Strike
2.500000
Counter-Strike Condition Zero
2.000000
Counter-Strike Global Offensive
3.285714
Counter-Strike Nexon Zombies
1.500000
Counter-Strike Source
2.250000
Crash Time II
3.000000
Creativerse
4.000000
Crusader Kings II
4.000000
Cry of Fear
3.000000
Crypt of the NecroDancer
4.000000
D.I.P.R.I.P. Warm Up
2.000000
DARK SOULS II
3.500000
DARK SOULS II Scholar of the First Sin
3.000000
Dark Souls Prepare to Die Edition
3.000000
Darksiders II
4.000000
Day of Defeat
2.000000
Day of Defeat Source
2.000000
DayZ
1.500000
DC Universe Online
1.500000
Dead Island
3.666667
Dead Island Epidemic
2.500000
Dead Island Riptide
3.000000
Dead Rising 2
5.000000
Dead Rising 3
3.000000
Deadlight
3.000000
Defiance
1.000000
Dino D-Day
1.000000
DiRT 3 Complete Edition
4.000000
Dishonored
4.000000
Dishonored (RU)
2.000000
Don't Starve
3.500000
Don't Starve Together Beta
3.000000
Dota 2
2.000000
Duke Nukem 3D Megaton Edition
3.000000
Dungeon Defenders
4.000000
Dungeon Defenders II
4.000000
Dungeon Siege
5.000000
Dungeons of Dredmor
4.000000
E.Y.E Divine Cybermancy
5.000000
Empire Total War
3.000000
Endless Sky
3.000000
Endless Space
4.000000
Euro Truck Simulator 2
3.166667
Europa Universalis IV
4.000000
EVGA PrecisionX 16
1.000000
F.E.A.R.
4.000000
Fable - The Lost Chapters
3.000000
Fable III
4.000000
Fallout 3 - Game of the Year Edition
5.000000
Fallout 4
3.000000
Fallout New Vegas
3.333333
Far Cry 3
3.333333
Far Cry 4
5.000000
Farming Simulator 15
2.500000
Farming Simulator 2013
3.000000
FEZ
3.000000
FINAL FANTASY VII
5.000000
FINAL FANTASY XIII-2
5.000000
Fistful of Frags
2.000000
FlatOut 2
5.000000
FlatOut Ultimate Carnage
4.000000
Football Manager 2009
5.000000
Football Manager 2010
4.000000
Football Manager 2011
5.000000
Football Manager 2012
4.500000
Football Manager 2013
4.500000
Football Manager 2014
4.000000
Football Manager 2015
4.000000
Football Manager 2016
5.000000
FORCED
4.500000
From Dust
3.000000
FTL Faster Than Light
3.000000
Fuse
3.000000
Galactic Civilizations II Ultimate Edition
2.000000
Game Dev Tycoon
2.500000
Game of Thrones
4.000000
GameMaker Studio
2.000000
Garry's Mod
2.500000
Geometry Dash
5.000000
Goat Simulator
3.000000
Godus
4.000000
Gotham City Impostors
5.000000
Gotham City Impostors Free To Play
3.000000
Grand Theft Auto IV
3.000000
Grand Theft Auto San Andreas
2.000000
Grand Theft Auto V
3.400000
Grand Theft Auto Vice City
2.000000
Guild Wars
3.000000
Gunpoint
4.000000
H1Z1
3.000000
Half-Life
3.000000
Half-Life 2
4.000000
Half-Life 2 Deathmatch
2.000000
Half-Life 2 Episode One
3.333333
Half-Life 2 Episode Two
3.666667
Half-Life 2 Lost Coast
3.000000
Half-Life 2 Update
5.000000
HAWKEN
2.000000
Heroes & Generals
2.000000
HOARD
4.000000
Homefront
4.000000
Homeworld Remastered Collection
1.500000
How to Survive
3.000000
I am Bread
4.000000
Infestation Survivor Stories
3.000000
Infinite Crisis
1.000000
Injustice Gods Among Us Ultimate Edition
4.000000
Insurgency
3.000000
Just Cause 2
2.666667
Killing Floor
3.500000
Killing Floor 2
3.000000
Killing Floor Mod Defence Alliance 2
4.000000
King Arthur Collection
3.000000
Knights of Pen and Paper +1
5.000000
Left 4 Dead 2
2.000000
Legend of Grimrock
2.000000
LEGO Jurassic World
5.000000
LIGHTNING RETURNS FINAL FANTASY XIII
3.000000
Loadout
1.500000
Mafia II
3.000000
Magic 2014
3.000000
Magic Duels
3.000000
Magic The Gathering Duels of the Planeswalkers 2012
3.000000
Magicka
4.000000
Magicka Wizard Wars
2.000000
Marvel Heroes 2015
1.000000
Max Payne 3
4.000000
McPixel
4.000000
MechWarrior Online
2.000000
Medal of Honor(TM) Multiplayer
5.000000
Medal of Honor(TM) Single Player
5.000000
Medieval Engineers
3.000000
Medieval II Total War
4.000000
Medieval II Total War Kingdoms
3.000000
Men of War Assault Squad
3.000000
METAL GEAR SOLID V GROUND ZEROES
5.000000
METAL GEAR SOLID V THE PHANTOM PAIN
3.500000
Metro 2033
2.000000
Microsoft Flight Simulator X Steam Edition
3.000000
Middle-earth Shadow of Mordor
3.000000
Minecraft Story Mode - A Telltale Games Series
5.000000
Mitos.is The Game
5.000000
Monaco
4.000000
Monday Night Combat
5.000000
Mount & Blade
3.000000
Mount & Blade Warband
3.000000
Mount & Blade With Fire and Sword
3.000000
Murder Miners
5.000000
Natural Selection 2
2.000000
Need for Speed Hot Pursuit
3.000000
Need for Speed SHIFT
3.000000
NEKOPARA Vol. 0
5.000000
NEKOPARA Vol. 1
5.000000
NEOTOKYO
3.000000
Neverwinter
2.000000
Neverwinter Nights 2 Platinum
4.000000
No More Room in Hell
3.000000
Nosgoth
2.000000
Nuclear Dawn
3.000000
Nuclear Throne
3.000000
Octodad Dadliest Catch
4.000000
Orcs Must Die!
4.000000
Orcs Must Die! 2
3.500000
Ori and the Blind Forest
3.000000
ORION Prelude
2.000000
Outlast
3.000000
PAC-MAN Championship Edition DX+
4.000000
Path of Exile
2.333333
PAYDAY 2
3.400000
PAYDAY The Heist
4.000000
Pid
4.000000
Pinball FX2
3.000000
Pirates, Vikings, & Knights II
5.000000
Pixel Piracy
2.500000
PixelJunk Eden
1.000000
Plague Inc Evolved
4.000000
PlanetSide 2
2.000000
Poker Night at the Inventory
3.000000
Port Royale 3
3.000000
Portal
3.333333
Portal 2
3.142857
Portal Stories Mel
4.500000
Post Apocalyptic Mayhem
5.000000
Quake Live
3.000000
R.U.S.E
3.000000
RACE 07
4.000000
RaceRoom Racing Experience
3.000000
Red Faction Armageddon
3.000000
Red Faction Guerrilla Steam Edition
4.000000
Red Orchestra 2 Heroes of Stalingrad - Single Player
3.000000
RIFT
2.000000
Rise of Nations Extended Edition
4.000000
Rising Storm/Red Orchestra 2 Multiplayer
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5.000000
Star Wars Republic Commando
4.000000
Starbound
3.000000
State of Decay
3.000000
Stranded Deep
2.000000
Strike Suit Zero
4.000000
Stronghold 2
3.000000
Stronghold 3
4.500000
Stronghold Crusader HD
3.000000
Stronghold HD
5.000000
Stronghold Legends
3.000000
Super Crate Box
4.000000
Super Killer Hornet Resurrection
4.000000
Super Meat Boy
2.333333
Supreme Commander 2
3.000000
Supreme Commander Forged Alliance
3.000000
Survarium
2.000000
Tabletop Simulator
3.000000
Team Fortress 2
1.888889
TERA
2.000000
Terraria
2.600000
The Bard's Tale
2.500000
The Binding of Isaac
2.000000
The Binding of Isaac Rebirth
5.000000
The Bridge
3.000000
The Cave
3.000000
The Crew
4.000000
The Elder Scrolls III Morrowind
2.500000
The Elder Scrolls IV Oblivion
3.000000
The Forest
3.000000
The Long Dark
3.500000
The Lord of the Rings War in the North
2.000000
The Sims(TM) 3
3.000000
The Stanley Parable
5.000000
The Swapper
4.000000
The Walking Dead Season Two
3.000000
The Witcher 2 Assassins of Kings Enhanced Edition
2.500000
The Witcher 3 Wild Hunt
3.000000
The Witcher Enhanced Edition
2.000000
They Bleed Pixels
3.000000
Thomas Was Alone
3.000000
Ticket to Ride
2.000000
Tiny and Big Grandpa's Leftovers
5.000000
Titan Quest
2.000000
Toki Tori 2+
1.000000
Tom Clancy's Ghost Recon Phantoms - EU
2.000000
Tom Clancy's Ghost Recon Phantoms - NA
2.000000
Tomb Raider
3.000000
Toribash
3.000000
Total War ATTILA
2.000000
Total War ROME II - Emperor Edition
3.000000
Total War SHOGUN 2
2.666667
TowerFall Ascension
5.000000
Town of Salem
4.000000
Toy Soldiers
2.000000
TrackMania Stadium
3.500000
TrackMania United
5.000000
Train Fever
5.000000
Trainz Simulator 12
4.000000
Trials Evolution Gold Edition
5.000000
Trine 2
4.000000
Tropico 4
3.000000
Tropico 5
3.500000
Two Worlds II
4.000000
Ultra Street Fighter IV
3.000000
Undertale
4.000000
Universe Sandbox
3.000000
Unturned
2.600000
Valkyria Chronicles
3.000000
Victoria II
3.500000
Villagers and Heroes
5.000000
Waking Mars
1.000000
War of the Roses
3.000000
War Thunder
2.333333
Warframe
1.666667
Wargame European Escalation
2.000000
Wargame Red Dragon
2.000000
Warhammer 40,000 Dawn of War II Retribution
2.000000
Wolfenstein The New Order
3.000000
Worms Reloaded
2.500000
Worms Revolution
4.000000
XCOM Enemy Unknown
3.000000
You Have to Win the Game
1.000000
Zombie Panic Source
2.000000 Best UBCF Model: ubcf_model_3 (0.8189319) as its the lowest number.
Best IBCF Model: ibcf_model_6 (MAE = 1.140654) as its the lowest numebr
``` ## Part 8
They could use this collaborative filtering model by offering new games recommendations based on their previous gaming purchases. Could also tailor sales and promotions to specific audiences based on their personal refernces.