👉 Rating computing is the process of quantifying subjective evaluations or opinions into numerical values, typically ranging from 0 to 1 or -1 to 1, to facilitate comparison and analysis. In machine learning and data science, it's often used for tasks like sentiment analysis, where text data (like reviews or comments) is converted into scores that reflect the intensity of emotions or opinions expressed. This involves training models on labeled datasets where each piece of text is associated with a rating, and then using these models to predict ratings for new, unseen data. The goal is to create a continuous or discrete numerical representation that captures the essence of the subjective input, allowing for more effective decision-making and insights.
