binaryRatingMatrix-class: Class "binaryRatingMatrix": A Binary Rating Matrix

In recommenderlab: Lab for Developing and Testing Recommender Algorithms

Class "binaryRatingMatrix": A Binary Rating Matrix

Description

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.

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")

See Also

itemMatrix in arules, getList.

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

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

## coerce it into a binaryRatingMatrix
b <- as(m, "binaryRatingMatrix")
b

## coerce it back to see if it worked
as(b, "matrix")

## use some methods defined in ratingMatrix
dim(b)
dimnames(b)

## counts
rowCounts(b) ## number of ratings per user
colCounts(b) ## number of ratings per item

## plot
image(b)

## sample and subset
sample(b,2)
b[1:2,1:5]

## coercion
as(b, "list")
head(as(b, "data.frame"))
head(getData.frame(b, ratings=FALSE))

## 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
b2 <- as(df, "binaryRatingMatrix")
b2
as(b2, "matrix")

recommenderlab documentation built on Oct. 5, 2026, 9:08 a.m.