R/fcm-classes.R
, R/fcm-subsetting.R
fcm-class.Rd
The fcm class of object is a special type of fcm object with additional slots, described below.
# S4 method for fcm
t(x)
# S4 method for fcm,numeric
Arith(e1, e2)
# S4 method for numeric,fcm
Arith(e1, e2)
# S4 method for fcm,index,index,missing
[(x, i, j, ..., drop = TRUE)
# S4 method for fcm,index,index,logical
[(x, i, j, ..., drop = TRUE)
# S4 method for fcm,missing,missing,missing
[(x, i, j, ..., drop = TRUE)
# S4 method for fcm,missing,missing,logical
[(x, i, j, ..., drop = TRUE)
# S4 method for fcm,index,missing,missing
[(x, i, j, ..., drop = TRUE)
# S4 method for fcm,index,missing,logical
[(x, i, j, ..., drop = TRUE)
# S4 method for fcm,missing,index,missing
[(x, i, j, ..., drop = TRUE)
# S4 method for fcm,missing,index,logical
[(x, i, j, ..., drop = TRUE)
the fcm object
first quantity in "+" operation for fcm
second quantity in "+" operation for fcm
index for features
index for features
additional arguments not used here
always set to FALSE
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
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
# 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, ]
#> Feature co-occurrence matrix of: 3 by 12 features.
#> features
#> features this contains lots of stopwords no if and or but
#> this 0 1 1 1 1 0 0 0 0 0
#> contains 0 0 1 1 1 0 0 0 0 0
#> lots 0 0 0 1 1 1 1 1 1 1
#> [ reached max_nfeat ... 2 more features ]
fcmat[4:5, 1:5]
#> Feature co-occurrence matrix of: 2 by 5 features.
#> features
#> features this contains lots of stopwords
#> of 0 0 0 0 1
#> stopwords 0 0 0 0 0