The template project for three and five way sentiment classification.
If you are looking to integrate natural language processing APIs or modules into your projects, check this repo out: https://github.com/semanticanalyzer/nlproc_sdk_sample_code
In order to utilize the kaggle's training set the code is using you need to accept the terms and conditions of the competition and put the training set train.csv into the kaggle directory.
The three way model trained using unigrams is as good as the following stats:
Correctly Classified Instances 28625 83.3455 % Incorrectly Classified Instances 5720 16.6545 % Kappa statistic 0.4643 Mean absolute error 0.2354 Root mean squared error 0.3555 Relative absolute error 71.991 % Root relative squared error 87.9228 % Coverage of cases (0.95 level) 97.7697 % Mean rel. region size (0.95 level) 83.3426 % Total Number of Instances 34345
The same training for five way model shows:
Correctly Classified Instances 104814 67.1626 % Incorrectly Classified Instances 51246 32.8374 % Kappa statistic 0.4883 Mean absolute error 0.1916 Root mean squared error 0.3111 Relative absolute error 72.6628 % Root relative squared error 85.6599 % Coverage of cases (0.95 level) 96.3732 % Mean rel. region size (0.95 level) 60.9708 % Total Number of Instances 156060
Feel free to fork and use the code the way you want. The license is ASL 2.0.