Paper: Text Categorization with Support Vector Machines: Learning with Many Relevant Features
Source: https://dl.acm.org/citation.cfm?id=649721
The paper suggests the suitability of Support Vector Machines for text classification purposes. In this jupyter notebook I tried to reproduce the results obtained in the paper. Here is a small sample from the notebook:
F1-Scores from reproduction
Datasets:
- Reuters: http://disi.unitn.it/moschitti/corpora/Reuters21578-Apte-90Cat.tar.gz
- Ohsumed: http://disi.unitn.it/moschitti/corpora/ohsumed-first-20000-docs.tar.gz
Unzip the datasets into a directory called ./datasets
Note: This notebook needs a Python 2 kernel because of the svmlight package and if you don't want to do the training yourself the results are stored in ./results.tar.gz