So I have the following data:
I have one series where each word has a value that describes the average review score that would get.
For example, if the word "excellent" showed up in reviews with a score of 2,3,5,4 it would gain a value of 3.5.
I also have a list of the words contained in a review, and the review scores of each of those written reviews.
Unique_words ["good","clean","hotel","enjoyed","stay","here"] score 4
(These are ofc simplified examples, my actual data is a lot longer)
I also have the original reviews, from which the unique_words are taken from.
The question is, how would I use this data in order to train a machine-learning algorithm to predict what score a review would get, given the unique words contained inside it.