how to get stylometric feature from text( for task of author attribution)
Many studies have shown that the frequency and distribution of FUNCTION WORDS is significant and indicative of individual style. FUNCTION WORDS are those with little or no LEXICAL MEANING: articles THE, AN, A, conjunctions, personal pronouns, auxiliary verbs. etc.
I try to get text features for stylometry task in identifying the author of the given text.
I check for :

text length by word
text length by character
punctuation count
unique word count
etc...
but in classifying this feature give unreasonable results, so:
i want to check more features...
I have two questions:


Is there any good feature that I forget to extract from text to help classifying result
I have a data frame like this:
text ,                  author ,    pos
i go to school   ,        x  ,       [N,V,...]
..
we are good   ,     y      ,    [N,V,ADj]

my question is that how can I get good feature from pos column? for example the ratio of "N" to other? or some thing like this...
how to improve this multi_input single_lable multi_class classification result? with which feature? is there any good source?