  A lot of news sources picked up on Typhoon Rai (also known locally as Typhoon
Odette), along with fake news outlets. The study honed in on the issue, to
create a model that can identify between legitimate and illegitimate news
articles. With this in mind, we chose the following machine learning algorithms
in our development: Logistic Regression, Random Forest and Multinomial Naive
Bayes. Bag of Words, TF-IDF and Lemmatization were implemented in the Model.
Gathering 160 datasets from legitimate and illegitimate sources, the machine
learning was trained and tested. By combining all the machine learning
techniques, the Combined BOW model was able to reach an accuracy of 91.07%,
precision of 88.33%, recall of 94.64%, and F1 score of 91.38% and Combined
TF-IDF model was able to reach an accuracy of 91.18%, precision of 86.89%,
recall of 94.64%, and F1 score of 90.60%.
