Conducting sparse feature selection on arbitrarily long phrases in text corpora with a focus on interpretability
Table 12: Different Summaries of Carbon Monoxide (using stemming, compared to chemical family)
['phrase', 'q=1.2', 'q=1.5', 'q=2', 'q=3', 'q=4', '# reports', '# tagged', '% tagged', '% phrase']
We also analyzed the data using stemming. Results are again broadly similar (but possibly harder to read). Stemming collapses phrases, which can be helpful, but hampers human readability. Appendix A consists of supplemental tables showing alternate summaries of the case studies discussed above.