R: Virtual class "fcm" for a feature co-occurrence matrix

fcm-class {quanteda} | R Documentation

## Virtual class "fcm" for a feature co-occurrence matrix

### Description

The fcm class of object is a special type of fcm object with additional slots, described below.

### Usage

    ## S4 method for signature 'fcm'
    t(x)

    ## S4 method for signature 'fcm,numeric'
    Arith(e1, e2)

    ## S4 method for signature 'numeric,fcm'
    Arith(e1, e2)

    ## S4 method for signature 'fcm,index,index,missing'
    x[i, j, ..., drop = TRUE]

    ## S4 method for signature 'fcm,index,index,logical'
    x[i, j, ..., drop = TRUE]

    ## S4 method for signature 'fcm,missing,missing,missing'
    x[i, j, ..., drop = TRUE]

    ## S4 method for signature 'fcm,missing,missing,logical'
    x[i, j, ..., drop = TRUE]

    ## S4 method for signature 'fcm,index,missing,missing'
    x[i, j, ..., drop = TRUE]

    ## S4 method for signature 'fcm,index,missing,logical'
    x[i, j, ..., drop = TRUE]

    ## S4 method for signature 'fcm,missing,index,missing'
    x[i, j, ..., drop = TRUE]

    ## S4 method for signature 'fcm,missing,index,logical'
    x[i, j, ..., drop = TRUE]

### Arguments

`x` | the fcm object
`e1` | first quantity in "+" operation for fcm
`e2` | second quantity in "+" operation for fcm
`i` | index for features
`j` | index for features
`...` | additional arguments not used here
`drop` | always set to `FALSE`

### Slots

`context`

  the context definition

`window`

  the size of the window, if `context = "window"`

`count`

  how co-occurrences are counted

`weights`

  context weighting for distance from target feature, equal in length to `window`

`margin`

  frequencies of features in the original dfm or tokens

`tri`

  whether the lower triangle of the symmetric V \times V matrix is recorded

`ordered`

  whether a term appears before or after the target feature are counted separately

### See Also

fcm

### Examples

    # fcm subsetting
    fcmat <- fcm(tokens(c("this contains lots of stopwords",
                      "no if, and, or but about it: lots"),
                    remove_punct = TRUE))
    fcmat[1:3, ]
    fcmat[4:5, 1:5]

[Package quanteda version 3.0.0 Index]