Preprocessed 396 tweets. Fraction positive: 0.38636363
=== Syntax highlighting ===
You can also highlight snippets of text, we use the excellent [[http://www.pygments.org/|Pygments]] library.
Here's an example of some Python code:
- formatter = lambda t: "funky"+t
+$ updown lex-ratio -g data/stanford/stanford-features.txt -p src/main/resources/eng/lexicon/subjclueslen1polar.tff
-You can check out the source of this page to see how that's done, and make sure to bookmark [[http://pygments.org/docs/lexers/|the vast library of Pygment lexers]], we accept the 'short name' or the 'mimetype' of anything in there.
+You should see the following output:
+***** PER TWEET EVAL *****
+58 tweets were abstained on; assuming half (29.0) were correct.
+Accuracy: 0.72131145 (132.0/183)
+***** PER USER EVAL *****
+Number of users evaluated: 0 (min of 3 tweets per user)
+Point the -g flag to other preprocessed feature files to run LexRatio on other datasets.