- The main purpose of this project is to write a machine learning program that is able to determine positive and negative natural language statements, according to some kind of classification technique. And see how accurate it will end up to be?
- Another goal for this project is to apply some different text pre-processing techniques on the training & testing sets we have, and see how this will affect our learning module and our accuracy ratio as an overall.
- System uses NLTK text classifiers (NaiveBayes, DecisionTree, MaxEntropy, MaxVote).
- Full Responsive Mobile Accessible HTML / CSS3 / JS web framework UI.
- Adding a layer of customization for the system’s parameters, to be customized due to the user preferences.
- Results view are customizable to user preferences.
- Flask installtion guides are inside the documentation file.
- This current version of the system is V2.0
- You can read about V1.0 in the documentation
- This was a project for class CSC 594 - Texting Mining (AI)
- For Technical details and bench mark results, please read the provided documentation.