Читать книгу Advanced Analytics and Deep Learning Models - Группа авторов - Страница 76

To implement this proposed approach, they have used Yahoo! Movies dataset. This dataset consists of 62,156 rating provides by 6,078 users on 976 movies. To make it simple, they have extracted those clients that have rated to minimum 20 movies. This condition satisfies 484 users and 945 movies, and they have total 19,050 ratings. Then, every client’s rating is splitted arbitrarily into training and testing set. They took 70% of data for training purpose and remaining 30% of data for testing purpose. Then, they calculate the distance between clients successfully. They selected top 30 most equivalent users for the neighborhood set formation. To evaluate this proposed approach, they used the most popular Mean Absolute Error (MAE) performance matrix. MAE is very popular because of its simplicity and accuracy as we have seen before. It matches the goal of the experiment. The mean absolute error estimates the derivation of actual and predicted client ratings [2].