itemMatrix-class {arules}R Documentation

Class itemMatrix — Sparse Binary Incidence Matrix to Represent Sets of Items

Description

The itemMatrix class is the basic building block for transactions, and associations. The class contains a sparse Matrix representation of a set of itemsets and the corresponding item labels.

Usage

## S4 method for signature 'itemMatrix'
summary(object, maxsum = 6, ...)

## S4 method for signature 'itemMatrix'
dim(x)

nitems(x, ...)

## S4 method for signature 'itemMatrix'
nitems(x)

## S4 method for signature 'itemMatrix'
length(x)

toLongFormat(from, ...)

## S4 method for signature 'itemMatrix'
toLongFormat(from, cols = c("ID", "item"), decode = TRUE)

## S4 method for signature 'itemMatrix'
labels(object, itemSep = ",", setStart = "{", setEnd = "}")

itemLabels(object, ...)

itemLabels(object) <- value

## S4 method for signature 'itemMatrix'
itemLabels(object)

## S4 replacement method for signature 'itemMatrix'
itemLabels(object) <- value

itemInfo(object)

itemInfo(object) <- value

## S4 method for signature 'itemMatrix'
itemInfo(object)

## S4 replacement method for signature 'itemMatrix'
itemInfo(object) <- value

itemsetInfo(object)

itemsetInfo(object) <- value

## S4 method for signature 'itemMatrix'
itemsetInfo(object)

## S4 replacement method for signature 'itemMatrix'
itemsetInfo(object) <- value

## S4 method for signature 'itemMatrix'
dimnames(x)

## S4 replacement method for signature 'itemMatrix,list'
dimnames(x) <- value

Arguments

object, x, from

the object.

maxsum

integer, how many items should be shown for the summary?

...

further parameters

cols

columns for the long format.

decode

decode item IDs to item labels.

itemSep

item separator symbol.

setStart

set start symbol.

setEnd

set end symbol.

value

replacement value

Details

Representation

Sets of itemsets are represented as a compressed sparse binary matrix. Conceptually, columns represent items and rows are the sets/transactions. In the compressed form, each itemset is a vector of column indices (called item IDs) representing the items.

Warning: Ideally, we would store the matrix as a row-oriented sparse matrix (ngRMatrix), but the Matrix package provides better support for column-oriented sparse classes (ngCMatrix). The matrix is therefore internally stored in transposed form.

Working with several itemMatrix objects

If you work with several itemMatrix objects at the same time (e.g., several transaction sets, lhs and rhs of a rule, etc.), then the encoding (itemLabes and order of the items in the binary matrix) in the different itemMatrices is important and needs to conform. See itemCoding to learn how to encode and recode itemMatrix objects.

Functions

Slots

data

a sparse matrix of class ngCMatrix representing the itemsets. Warning: the matrix is stored in transposed form for efficiency reasons!.

itemInfo

a data.frame

itemsetInfo

a data.frame

Objects from the Class

Objects can be created by calls of the form new("itemMatrix", ...). However, most of the time objects will be created by coercion from a matrix, list or data.frame.

Coercions

Warning: the ngCMatrix representation is transposed!

Author(s)

Michael Hahsler

See Also

Other itemMatrix and transactions functions: abbreviate(), crossTable(), c(), duplicated(), extract, hierarchy, image(), inspect(), is.superset(), itemFrequencyPlot(), itemFrequency(), match(), merge(), random.transactions(), sample(), sets, size(), supportingTransactions(), tidLists-class, transactions-class, unique()

Examples

set.seed(1234)

## Generate a logical matrix with 5000 random itemsets for 20 items
m <- matrix(runif(5000 * 20) > 0.8, ncol = 20,
            dimnames = list(NULL, paste("item", c(1:20), sep = "")))
head(m)

## Coerce the logical matrix into an itemMatrix object
imatrix <- as(m, "itemMatrix")
imatrix

## An itemMatrix contains a set of itemsets (each row is an itemset).
## The length of the set is the number of rows.
length(imatrix)

## The sparese matrix also has regular matrix  dimensions.
dim(imatrix)
nrow(imatrix)
ncol(imatrix)

## Subsetting: Get first 5 elements (rows) of the itemMatrix. This can be done in
## several ways.
imatrix[1:5]            ### get elements 1:5
imatrix[1:5, ]          ### Matrix subsetting for rows 1:5
head(imatrix, n = 5)    ### head()

## Get first 5 elements (rows) of the itemMatrix as list.
as(imatrix[1:5], "list")

## Get first 5 elements (rows) of the itemMatrix as matrix.
as(imatrix[1:5], "matrix")

## Get first 5 elements (rows) of the itemMatrix as sparse ngCMatrix.
## **Warning:** For efficiency reasons, the ngCMatrix is transposed! You
## can transpose it again to get the expected format.
as(imatrix[1:5], "ngCMatrix")
t(as(imatrix[1:5], "ngCMatrix"))

## Get labels for the first 5 itemsets (first default and then with
## custom formating)
labels(imatrix[1:5])
labels(imatrix[1:5], itemSep = " + ", setStart = "", setEnd = "")

## Create itemsets manually from an itemMatrix. Itemsets contain items in the form of
## an itemMatrix and additional quality measures (not supplied in the example).
is <- new("itemsets", items = imatrix)
is
inspect(head(is, n = 3))


## Create rules manually. I use imatrix[4:6] for the lhs of the rules and
## imatrix[1:3] for the rhs. Rhs and lhs cannot share items so I use
## itemSetdiff here. I also assign missing values for the quality measures support
## and confidence.
rules <- new("rules",
             lhs = itemSetdiff(imatrix[4:6], imatrix[1:3]),
             rhs = imatrix[1:3],
             quality = data.frame(support = c(NA, NA, NA),
                                  confidence =  c(NA, NA, NA)
          ))
rules
inspect(rules)

## Manually create a itemMatrix with an item encoding that matches imatrix (20 items in order
## item1, item2, ..., item20)
itemset_list <- list(c("item1","item2"),
                     c("item3"))

imatrix_new <- encode(itemset_list, itemLabels = imatrix)
imatrix_new
compatible(imatrix_new, imatrix)
[Package arules version 1.7-7 Index]