Virtual class "dfm" for a document-feature matrix

Source: R/dfm-classes.R, R/dfm-subsetting.R

The dfm class of object is a type of Matrix-class object with additional slots, described below. quanteda uses two subclasses of the dfm class, depending on whether the object can be represented by a sparse matrix, in which case it is a dfm class object, or if dense, then a dfmDense object. See Details.

# S4 method for class 'dfm'
t(x)

# S4 method for class 'dfm'
colSums(x, na.rm = FALSE, dims = 1, ...)

# S4 method for class 'dfm'
rowSums(x, na.rm = FALSE, dims = 1, ...)

# S4 method for class 'dfm'
colMeans(x, na.rm = FALSE, dims = 1, ...)

# S4 method for class 'dfm'
rowMeans(x, na.rm = FALSE, dims = 1, ...)

# S4 method for class 'dfm,numeric'
Arith(e1, e2)

# S4 method for class 'numeric,dfm'
Arith(e1, e2)

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

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

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

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

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

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

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

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

Arguments

x

the dfm object

na.rm

if TRUE, omit missing values (including NaN) from the calculations

dims

ignored

...

additional arguments not used here

e1

first quantity in an Arith operation for dfm

e2

second quantity in an Arith operation for dfm

i

document names or indices for documents to extract.

j

feature names or indices for documents to extract.

Details

The dfm class is a virtual class that will contain dgCMatrix-class.

Slots

weightTf

the type of term frequency weighting applied to the dfm. Default is "frequency", indicating that the values in the cells of the dfm are simple feature counts. To change this, use the dfm_weight() method.

weightFf

the type of document frequency weighting applied to the dfm. See docfreq().

smooth

a smoothing parameter, defaults to zero. Can be changed using the dfm_smooth() method.

Dimnames

These are inherited from Matrix-class but are named docs and features respectively.

See also

dfm

Examples

# dfm subsetting
dfmat <- dfm(tokens(c("this contains lots of stopwords",
                  "no if, and, or but about it: lots",
                  "and a third document is it"),
                remove_punct = TRUE))
dfmat[1:2, ]
#> Document-feature matrix of: 2 documents, 16 features (59.38% sparse) and 0 docvars.
#>        features
#> docs    this contains lots of stopwords no if and or but
#>   text1    1        1    1  1         1  0  0   0  0   0
#>   text2    0        0    1  0         0  1  1   1  1   1
#> [ reached max_nfeat ... 6 more features ]
dfmat[1:2, 1:5]
#> Document-feature matrix of: 2 documents, 5 features (40.00% sparse) and 0 docvars.
#>        features
#> docs    this contains lots of stopwords
#>   text1    1        1    1  1         1
#>   text2    0        0    1  0         0