During week 5, I met with my external advisor to discuss the progress I have made thus far. He helped me by giving me a few links to learn how to implement a classifier into my project, which is the machine learning model. I first started using a pattern matcher my external advisor to split the article into sentences, which was more accurate than the pattern matcher I used to split the article into sentences.
After successfully splitting the article into different sentences and getting the correct output from the FeatureExtractor class, I started creating the classifier. I used the Stanford CoreNLP library’s github to help me create the classifier. After I created the classifier, I had to figure out what the output meant and had to figure out how to make the run time of my code shorter. For the rest of the week, I was just testing my features and its topic in the classifier and seeing how accurate it is.
Next week, I will be testing my classifier even more and trying to find a way to make my program run faster.
Thanks for reading!