Skip to content

Latest commit

 

History

History
47 lines (33 loc) · 1.14 KB

README.md

File metadata and controls

47 lines (33 loc) · 1.14 KB

emoticat

Emotion Categorization

Running : We are using sbt. If you have trouble with the dependencies or any general questions, contact Ausitn

 > sbt
 > compile
 > project
 > run

As an example

 > sbt
 > compile
 > project polarity
 > run-main main.scala.PolarityDistribution Tweet-Data/Tiny-Labeled.csv Tweet-Data/Tiny-Polarity.ser
 > run-main main.scala.CalculatePolarities -s Tweet-Data/Tiny-Polarity.ser Tweet-Data/Tiny-Unlabeled.csv Tweet-Data/Tiny-features.txt

If you are running a very large dataset, you should modify your sbt configuration to increase RAM, ie,

#!/bin/sh
test -f ~/.sbtconfig && . ~/.sbtconfig
exec java -Xmx400G -Xms20G -XX:MaxPermSize=40G ${SBT_OPTS} -jar ~/bin/sbt-launch.jar "$@"

Todo : describe how to run liblinear / libsvm

Testing :

We are using scalatest for testing. From the root directory :

 > sbt test

Should run and compile all test. You can also test within a specific project, or use test-only to call a specific test.

Todo :

  • Unit Tests
  • Streaming Support
  • Documentation Auto-generation
  • Maven for external jar/lib handling