Hi all, I have a question about the arules package in R. I hope the example
tables are readable in your email, otherwise you can view it in the
question.txt in the attachment.Within the apriori function in the arules
package, I want the outcome to only contain these two variables in the LHS
HouseOwnerFlag=0 and HouseOwnerFlag=1. The RHS should only contain attributes
from the column Product. For instance: lhs rhs
support confidence lift1 {HouseOwnerFlag=0} =>
{Product=SV 16xDVD M360 Black} 0.2500000 0.2500000 1.0000002
{HouseOwnerFlag=1} => {Product=Adventure Works 26" 720p} 0.2500000
0.2500000 1.0000003 {HouseOwnerFlag=0} => {Product=Litware Wall Lamp E3015
Silver}0.1666667 0.3333333 1.3333334 {HouseOwnerFlag=1} => {Product=Contoso
Coffee Maker 5C E0900} 0.1666667 0.3333333 1.333333So now I use the following:
rules <- apriori(sales, parameter=list(support =0.01, confidence =0.8,
minlen=2), appearance = list(lhs=c("HouseOwnerFlag=0",
"HouseOwnerFlag=1")))Then I use this to ensure that only the Product column is
on the RHS: inspect( subset( rules, subset = rhs %pin% "Product=" ) )The
outcome is like this (for the sake of readability, I omitted the colomns for
support, lift, confidence): lhs
rhs 1 {ProductKey=153, IncomeGroup=Moderate,
BrandName=Adventure Works } => {Product=SV 16xDVD M360 Black} 2
{ProductKey=176, MaritalStatus=M, ProductCategoryName=TV and Video } =>
{Product=Adventure Works 26" 720p} 3 {BrandName=Southridge Video,
NumberChildrenAtHome=0 } => {Product=Litware Wall Lamp E3015
Silver} 4 {HouseOwnerFlag=1, BrandName=Southridge Video, ProductKey=170 }
=> {Product=Contoso Coffee Maker 5C E0900} So apparently the LHS is able to
contain every possible column, not just HouseOwnerFlag like I specified. I see
that I can put default="rhs" in the apriori function to prevent this, like so:
rules <- apriori(sales, parameter=list(support =0.001, confidence =0.5,
minlen=2), appearance = list(lhs=c("HouseOwnerFlag=0", "HouseOwnerFlag=1"),
default="rhs")) Then upon inspecting (without the subset part, just
inspect(rules), there are far less rules (7) than before but it does indeed
only containHouseOwnerFlag in the LHS: lhs rhs
support confidence lift1 {HouseOwnerFlag=0} =>
{MaritalStatus=S} 0.2500000 0.2500000 1.0000002
{HouseOwnerFlag=1} => {Gender=M} 0.2500000 0.2500000
1.0000003 {HouseOwnerFlag=0} => {NumberChildrenAtHome=0} 0.1666667
0.3333333 1.3333334 {HouseOwnerFlag=1} => {Gender=M}
0.1666667 0.3333333 1.333333However on the RHS there's nothing from the column
Product in the RHS. So it has no use to inspect it with subset as ofcourse it
would return null. I tested it several times with different support numbers to
experiment and see if Product would appear or not, but the 7 same rules remain
the same.So my question is, how can I specify both the LHS (HouseOwnerFlag) and
RHS (Product)? What am I doing wrong?You can reproduce this problem by
downloading this testdataset from the attachment (testdf.txt) or via this
link:https://www.dropbox.com/s/tax5xalac5xgxtf/testdf.txt?dl=0 Mind you, I only
took the first 20 rows from a huge dataset (12 million), so the output here
won't have the same product names as the example I displayed above. But the
problem still remains the same. (if you would like to have the entire dataset I
can email it ofcourse). I want to be able to get only HouseOwnerFlag=0 and/or
HouseOwnerFlag=1 on the LHS and the column Product on the RHS. I asked this
question on other forum before, but no response at all unfortunately. Since
this mailinglist is dedicated to R only I thought you guys might be able to
help me. Thanks in advance! I look forward to hear from you.Kim
sales <- structure(list(ProductCategoryName = structure(c(6L, 6L, 2L,
2L, 2L, 7L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L,
2L), .Label = c("Audio",
"Cameras and camcorders ", "Cell phones",
"Computers",
"Games and Toys", "Home Appliances", "Music, Movies and Audio Books",
"TV and
Video"), class = "factor"), ProductSubcategory = structure(c(26L,
26L, 11L, 12L, 12L, 21L,
27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L,
27L, 12L, 12L, 12L, 12L,
12L), .Label = c("Air Conditioners",
"Bluetooth Headphones", "Boxed Games", "Camcorders", "Cameras &
Camcorders Accessories",
"Car Video", "Cell phones Accessories", "Coffee Machines",
"Computers Accessories",
"Desktops", "Digital Cameras", "Digital SLR Cameras", "Download
Games",
"Fans", "Home & Office Phones", "Home Theater System", "Lamps",
"Laptops", "Microwaves", "Monitors", "Movie DVD", "MP4&MP3",
"Printers, Scanners & Fax", "Projectors & Screens", "Recording
Pen",
"Refrigerators", "Smart phones & PDAs ", "Televisions", "Touch
Screen Phones ",
"VCD & DVD", "Washers & Dryers", "Water Heaters"), class =
"factor"),
Product = structure(c(1L, 1L, 2L, 3L, 3L, 4L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
6L, 6L, 6L, 6L, 6L), .Label = c("Fabrikam
Refrigerator 4.6CuFt E2800 Grey",
"A. Datum Consumer Digital Camera M300 Orange", "Contoso SLR Camera M144
Gold", "SV DVD Movies E100 Yellow",
"The Phone Company Smart phones 160x160 M26 White", "Fabrikam SLR Camera 35
X358 Gold",
"WWI Wireless Transmitter and Bluetooth Headphones X250 White"
), class = "factor"), Region =
structure(c(30L, 30L, 30L,
30L, 30L, 30L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L), .Label = c("Armenia", "Australia", "Bhutan",
"Canada", "China", "France", "Germany", "Germany ",
"Greece ",
"India", "Iran", "Ireland ", "Italy ", "Japan",
"Kyrgyzstan",
"Pakistan", "Poland ", "Portugal", "Russia",
"Singapore",
"South Korea", "Spain", "Switzerland ", "Syria",
"Taiwan",
"Thailand", "the Netherlands", "Turkmenistan", "United
Kingdom",
"United States"), class = "factor"), Age =
structure(c(32L,
31L, 30L, 40L, 40L, 36L, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA), .Label = c("34", "35", "36", "37",
"38", "39", "40", "41", "42", "43", "44",
"45", "46", "47",
"48", "49", "50", "51", "52", "53", "54",
"55", "56", "57",
"58", "59", "60", "61", "62", "63", "64",
"65", "66", "67",
"68", "69", "70", "71", "72", "73", "74",
"75", "76", "77",
"78", "79", "80", "81", "82", "83", "84",
"85", "86", "87",
"88", "89", "90", "91", "92", "93", "94",
"95", "96", "97",
"98", "99", "101", "102", "103", "104"),
class = "factor"),
IncomeGroup = structure(c(3L, 3L, 3L, 3L, 3L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L), .Label = c("High",
"Low", "Moderate"), class = "factor"), BrandName =
structure(c(6L,
6L, 1L, 4L, 4L, 12L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,
14L, 6L, 6L, 6L, 6L, 6L), .Label = c("A. Datum", "Adventure Works",
"Adventure Works ", "Contoso",
"Contoso ", "Fabrikam", "Fabrikam ",
"Litware", "Litware ", "Northwind
Traders", "Proseware",
"Southridge Video", "Tailspin Toys",
"The Phone Company",
"Wide World Importers"), class =
"factor"), MaritalStatus = structure(c(2L,
1L, 1L, 1L, 1L, 2L, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA,
NA, NA, NA, NA), .Label = c("M", "S"), class =
"factor"),
Gender = structure(c(1L, 1L, 1L, 1L, 2L, 2L, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA), .Label = c("F",
"M"), class = "factor"), TotalChildren = structure(c(3L,
3L, 5L, 4L,
4L, 6L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA,
NA), .Label = c("0", "1", "2", "3", "4", "5"), class = "factor"),
NumberChildrenAtHome = structure(c(2L, 2L, 3L, 1L, 1L, 1L,
NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA), .Label = c("0",
"1", "2", "3", "4", "5"), class =
"factor"), Education = structure(c(4L,
4L, 4L, 2L, 2L, 5L, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA,
NA, NA, NA, NA), .Label = c("Bachelors", "Graduate
Degree",
"High School", "Partial
College", "Partial High School"), class = "factor"),
Occupation = structure(c(4L, 4L, 4L, 2L, 2L, 5L, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA), .Label = c("Clerical",
"Management", "Manual", "Professional", "Skilled Manual"),
class = "factor"),
HouseOwnerFlag = structure(c(1L, 2L, 2L, 2L, 2L, 1L, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA), .Label = c("0",
"1"), class = "factor"), NumberCarsOwned =
structure(c(3L,
2L, 3L, 3L, 3L, 4L, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA), .Label = c("0", "1", "2", "3", "4"), class = "factor")),
.Names = c("ProductCategoryName",
"ProductSubcategory", "Product", "Region", "Age", "IncomeGroup",
"BrandName", "MaritalStatus", "Gender", "TotalChildren",
"NumberChildrenAtHome",
"Education", "Occupation", "HouseOwnerFlag", "NumberCarsOwned"
), row.names = c(NA, 20L), class = "data.frame")Hi all,
I have a question about the arules package in R. I hope the example tables are
readable in your email, otherwise you can view it in the question.txt in the
attachment.
Within the apriori function in the arules package, I want the outcome to only
contain these two variables in the LHS HouseOwnerFlag=0 and HouseOwnerFlag=1.
The RHS should only contain attributes from the column Product. For instance:
lhs rhs support
confidence lift
1 {HouseOwnerFlag=0} => {Product=SV 16xDVD M360 Black} 0.2500000
0.2500000 1.000000
2 {HouseOwnerFlag=1} => {Product=Adventure Works 26" 720p} 0.2500000
0.2500000 1.000000
3 {HouseOwnerFlag=0} => {Product=Litware Wall Lamp E3015 Silver}0.1666667
0.3333333 1.333333
4 {HouseOwnerFlag=1} => {Product=Contoso Coffee Maker 5C E0900} 0.1666667
0.3333333 1.333333
So now I use the following:
rules <- apriori(sales, parameter=list(support =0.01, confidence =0.8,
minlen=2), appearance = list(lhs=c("HouseOwnerFlag=0", "HouseOwnerFlag=1")))
Then I use this to ensure that only the Product column is on the RHS:
inspect( subset( rules, subset = rhs %pin% "Product=" ) )
The outcome is like this (for the sake of readability, I omitted the colomns
for support, lift, confidence):
lhs rhs
1 {ProductKey=153, IncomeGroup=Moderate, BrandName=Adventure Works } =>
{Product=SV 16xDVD M360 Black}
2 {ProductKey=176, MaritalStatus=M, ProductCategoryName=TV and Video } =>
{Product=Adventure Works 26" 720p}
3 {BrandName=Southridge Video, NumberChildrenAtHome=0 } =>
{Product=Litware Wall Lamp E3015 Silver}
4 {HouseOwnerFlag=1, BrandName=Southridge Video, ProductKey=170 } =>
{Product=Contoso Coffee Maker 5C E0900}
So apparently the LHS is able to contain every possible column, not just
HouseOwnerFlag like I specified. I see that I can put default="rhs" in the
apriori function to prevent this, like so:
rules <- apriori(sales, parameter=list(support =0.001, confidence =0.5,
minlen=2), appearance = list(lhs=c("HouseOwnerFlag=0", "HouseOwnerFlag=1"),
default="rhs"))
Then upon inspecting (without the subset part, just inspect(rules), there are
far less rules (7) than before but it does indeed only contain
HouseOwnerFlag in the LHS:
lhs rhs support
confidence lift
1 {HouseOwnerFlag=0} => {MaritalStatus=S} 0.2500000
0.2500000 1.000000
2 {HouseOwnerFlag=1} => {Gender=M} 0.2500000
0.2500000 1.000000
3 {HouseOwnerFlag=0} => {NumberChildrenAtHome=0} 0.1666667
0.3333333 1.333333
4 {HouseOwnerFlag=1} => {Gender=M} 0.1666667
0.3333333 1.333333
However on the RHS there's nothing from the column Product in the RHS. So it
has no use to inspect it with subset as ofcourse it would return null. I tested
it several times with different support numbers to experiment and see if
Product would appear or not, but the 7 same rules remain the same.
So my question is, how can I specify both the LHS (HouseOwnerFlag) and RHS
(Product)? What am I doing wrong?
You can reproduce this problem by downloading this testdataset from the
attachment or via this link:
https://www.dropbox.com/s/tax5xalac5xgxtf/testdf.txt?dl=0
Mind you, I only took the first 20 rows from a huge dataset (12 million), so
the output here won't have the same product names as the example I displayed
above. But the problem still remains the same. (if you would like to have the
entire dataset I can email it ofcourse). I want to be able to get only
HouseOwnerFlag=0 and/or HouseOwnerFlag=1 on the LHS and the column Product on
the RHS.
I asked this question on other forum before, but no response at all
unfortunately. Since this mailinglist is dedicated to R only I thought you guys
might be able to help me.
Thanks in advance! I look forward to hear from you.
Kim______________________________________________
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