Python Notebook For Board Games Review Predictor using Linear Regressor and Random Forest Techniques
Reviews can make or break a product; as a result, it becomes important for companies take drastic measures to ensure that their product receives good reviews. When it comes to board games, reviews and word-of-mouth are everything.
In this project, a linear regression model has been used to predict the average review a board game will receive based on characteristics such as minimum and maximum number of players, playing time, complexity, etc.
Used mean squared error as a performance metric to evaluate Linear regression model & ensemble model trained. Compared linear regressor model results with the performance of an ensemble method.