A simple F# demonstration of Automated Document Recognition using techniques like text tokenization, n-grams, TF-IDF weighting, CSV parsing, and text classification.
The code assumes the existence of some training data, in the form of plaintext files organized into folders by category:
- \TrainingData
- \CategoryA
- \Sample1.txt
- \Sample2.txt
- \CategoryB
- \SampleA.txt
- \CategoryA
...and a plain text file to be classified: "unknown.txt".
It also assumes the existence of a word whitelist CSV file, but this can be easily changed to a blacklist ("stopwords") or removed altogether.