In data flow, what does a Numeric Prediction model target?

A Numeric Prediction model specifically targets continuous values, which means it aims to predict quantities that can take any value within a given range. This could include measurements like sales figures, temperature readings, or any numerical data that is not confined to distinct categories.

In the context of data flow and predictive modeling, a Numeric Prediction model utilizes various algorithms and statistical techniques to analyze historical data, identify patterns, and make forecasts about future occurrences based on that continuous data. The precision and variability inherent in continuous values allow for a more nuanced understanding of trends and potential outcomes, distinguishing them significantly from the other types of targets mentioned. These other targets, such as categorized groups or binary outcomes, are not suitable for a Numeric Prediction model, which is specifically designed to handle and predict on a numerical continuum.