Class "binaryRatingMatrix": A Binary Rating Matrix

A matrix for binary rating data. A value of 1 indicates a positive rating; 0 indicates no rating or a negative rating. This coding is common for market-basket data, where products are either bought or not.

See also

itemMatrix in arules, getList.

Other rating data: dissimilarity, ratingMatrix-class, realRatingMatrix-class

Objects from the Class

Objects can be created by calls of the form new("binaryRatingMatrix", data = im), where im is an itemMatrix as defined in package arules, by coercion from a matrix (all non-zero values will be a 1), or by using binarize for an object of class "realRatingMatrix".

Slots

data:

Object of class "itemMatrix" (see package arules)

Extends

Class "ratingMatrix", directly.

Methods

coerce

signature(from = "matrix", to = "binaryRatingMatrix"): The matrix needs to be a logical matrix, or a 0-1 matrix (0 means FALSE and 1 means TRUE). NAs are interpreted as FALSE.

coerce

signature(from = "itemMatrix", to = "binaryRatingMatrix")

coerce

signature(from = "data.frame", to = "binaryRatingMatrix")

coerce

signature(from = "binaryRatingMatrix", to = "matrix")

coerce

signature(from = "binaryRatingMatrix", to = "dgTMatrix")

coerce

signature(from = "binaryRatingMatrix", to = "ngCMatrix")

coerce

signature(from = "binaryRatingMatrix", to = "dgCMatrix")

coerce

signature(from = "binaryRatingMatrix", to = "itemMatrix")

coerce

signature(from = "binaryRatingMatrix", to = "list")

% \item{dissimilarity}{\code{signature(x = "binaryRatingMatrix")}} % \item{LIST}{\code{signature(from = "binaryRatingMatrix")}: ... }

Examples

## create a 0-1 matrix
m <- matrix(sample(c(0,1), 50, replace=TRUE), nrow=5, ncol=10,
    dimnames=list(users=paste("u", 1:5, sep=''),
    items=paste("i", 1:10, sep='')))
m
#>      items
#> users i1 i2 i3 i4 i5 i6 i7 i8 i9 i10
#>    u1  1  1  0  1  0  0  0  1  1   0
#>    u2  0  1  1  1  0  0  0  0  0   0
#>    u3  0  1  1  0  1  0  1  1  0   0
#>    u4  0  0  0  1  0  0  1  1  0   0
#>    u5  1  1  0  1  1  0  1  0  0   1

## coerce it into a binaryRatingMatrix
b <- as(m, "binaryRatingMatrix")
b
#> 5 x 10 rating matrix of class ‘binaryRatingMatrix’ with 22 ratings.

## coerce it back to see if it worked
as(b, "matrix")
#>       i1    i2    i3    i4    i5    i6    i7    i8    i9   i10
#> u1  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE
#> u2 FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE
#> u3 FALSE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE FALSE FALSE
#> u4 FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE  TRUE FALSE FALSE
#> u5  TRUE  TRUE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE  TRUE

## use some methods defined in ratingMatrix
dim(b)
#> [1]  5 10
dimnames(b)
#> [[1]]
#> [1] "u1" "u2" "u3" "u4" "u5"
#> 
#> [[2]]
#>  [1] "i1"  "i2"  "i3"  "i4"  "i5"  "i6"  "i7"  "i8"  "i9"  "i10"
#> 

## counts
rowCounts(b) ## number of ratings per user
#> u1 u2 u3 u4 u5 
#>  5  3  5  3  6 
colCounts(b) ## number of ratings per item
#>  i1  i2  i3  i4  i5  i6  i7  i8  i9 i10 
#>   2   4   2   4   2   0   3   3   1   1 

## plot
image(b)


## sample and subset
sample(b,2)
#> 2 x 10 rating matrix of class ‘binaryRatingMatrix’ with 10 ratings.
b[1:2,1:5]
#> 2 x 5 rating matrix of class ‘binaryRatingMatrix’ with 6 ratings.

## coercion
as(b, "list")
#> $u1
#> [1] "i1" "i2" "i4" "i8" "i9"
#> 
#> $u2
#> [1] "i2" "i3" "i4"
#> 
#> $u3
#> [1] "i2" "i3" "i5" "i7" "i8"
#> 
#> $u4
#> [1] "i4" "i7" "i8"
#> 
#> $u5
#> [1] "i1"  "i2"  "i4"  "i5"  "i7"  "i10"
#> 
head(as(b, "data.frame"))
#>    user item rating
#> 1    u1   i1      1
#> 3    u1   i2      1
#> 9    u1   i4      1
#> 18   u1   i8      1
#> 21   u1   i9      1
#> 4    u2   i2      1
head(getData.frame(b, ratings=FALSE))
#>    user item
#> 1    u1   i1
#> 3    u1   i2
#> 9    u1   i4
#> 18   u1   i8
#> 21   u1   i9
#> 4    u2   i2

## creation from user/item tuples
df <- data.frame(user=c(1,1,2,2,2,3), items=c(1,4,1,2,3,5))
df
#>   user items
#> 1    1     1
#> 2    1     4
#> 3    2     1
#> 4    2     2
#> 5    2     3
#> 6    3     5
b2 <- as(df, "binaryRatingMatrix")
b2
#> 3 x 5 rating matrix of class ‘binaryRatingMatrix’ with 6 ratings.
as(b2, "matrix")
#>       1     2     3     4     5
#> 1  TRUE FALSE FALSE  TRUE FALSE
#> 2  TRUE  TRUE  TRUE FALSE FALSE
#> 3 FALSE FALSE FALSE FALSE  TRUE