Virtual class "fcm" for a feature co-occurrence matrix
The fcm class of object is a special type of fcm object with additional slots, described below.
## 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]
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 |
contextthe context definition
windowthe size of the window, if context = "window"
counthow co-occurrences are counted
weightscontext weighting for distance from target feature, equal in length to window
margintriwhether the lower triangle of the symmetric V \times V matrix is recorded
orderedwhether 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, ]
fcmat[4:5, 1:5]Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.