As I understand it when using seq2sparse with ng = 2 and ml = some large
number. This will never create a vector with less terms than words (all
other pars of the algorithm set aside). In other words ng = 2 and ml =
2000 will create very few n-grams but will never create a 0 length
vector unless there are no terms to begin with.
Is this correct?
I ask because it looks like many of my n-grams are not really helpful so
I keep tuning the ml upwards but Robin made a comment that this might
cause 0 length vectors, in which case I might want to stop using n-grams.