I'm working on a machine learning project aimed at predicting the quality/helpfulness of a review. For each review in the dataset, I have the review text, a number 'm' for the number of people who have voted on the review and a number 'n' for the number of positive votes on the review.
The goal is to predict the percentage of votes that are positive:
I'm using a random forest for the main algorithm, and trying to decide on what would be a good algorithm to use for the baseline.
A feature vector for each review comprises a word presence representation of the review and a number representing the total number of words in the review.
I would appreciate any suggestions on what algorithm would be good for a baseline method to compare against my random forest implementation.