The results are very encouraging.
Without feeding any rule to the computer, the following is the classification result
1. Major 5 samAsa types classification - 70%
2. Minor 55 samAsa subtypes classification - 55 %.
3. Major 5 samAsa types classification taking the first two entries - 85 %.
Probability of a fluke would be 1 - 20 %, 2 - 0.2 %, 40 %.
So, the machine learning is statistically significant, if not good enough.
The database which was used was scraped from
http://sanskrit.uohyd.ernet.in/Corpus/SHMT/Samaas-Tagging/ and randomly shuffled to homogenize the dataset.
The tool was developed for samAsa classification initially, but now generalized for any string classification problem.