Validate the internal structure of a DSM object and return a list with information about the object.
check.dsm(model, validate = FALSE, nonneg.check = FALSE)
an object of class dsm
carry out extended validation of internal consistency? (may be expensive)
if TRUE
, check the co-occurrence (\(M\)) and/or score (\(S\)) matrix for non-negativity (may be expensive)
Aborts with error message if any inconsistency is detected. Otherwise a list with the following items is returned:
number of rows (target terms) of the DSM
number of columns (features) of the DSM
sample size of the underlying data set (may be NA
)
whether co-occurrence frequency matrix \(M\) is available
whether \(M\) is sparse or dense (only present if M$ok
)
whether \(M\) is in canonical DSM format (only present if M$ok
)
whether \(M\) is non-negative (only present if M$ok
, and may be NA
unless nonneg.check=TRUE was specified
)
whether score matrix \(S\) is available
whether \(S\) is sparse or dense (only present if S$ok
)
whether \(S\) is in canonical DSM format (only present if S$ok
)
whether \(S\) is non-negative (only present if S$ok
, and may be NA
unless nonneg.check=TRUE was specified
)
TRUE
if matrix combines data with inconsistent row or column marginals (in this case, association scores cannot be computed any more)
# NOT RUN {
check.dsm(DSM_TermTerm)
# }
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