2 Problem
This project consists in the prediction of a quality score associated with a beer review. Practically, you are required to build a regression model capable of inferring the quality score assigned to the beer by the reviewer.
Warning: For this competition, you will not be allowed to use external datasets other than that provided for the competition. Adoption of external resources will result in failure of the exam.
2.1 Dataset
The dataset for this project contains beer reviews in tabular format. It counts 100,000 entries, each of which corresponds to a review expressed by a user on a website for beer benchmarks.
Each review is characterized by both numerical and categorical attributes. Each reviewer evaluates the beer on four different categories, namely appearance, aroma, palate and taste. A textual description is provided as well. Additionally, several information on the user is included. The quality score is reported on the feature named review/overall and is expressed as a number between 1 and 5. Half scores, such as 1.5, 2.5, etc., are allowed[1]. The dataset is located at: https://dbdmg.polito.it/wordpress/wp-content/uploads/2021/06/DSL_project_2021.zip Within the archive, you will find the following files:
• development.tsv (development set): a tab-separated values file containing the reviews from the development set. This portion does have the review/overall feature, which you should use to train and validate your models.
• evaluation.tsv (evaluation set): a tab-separated values file containing the reviews from the evaluation set. This portion does not have the review/overall feature.
2.2 Task
You are required to build a regression pipeline to assign an overall quality score to each record in the Evaluation set.
