Which of the following is an example of continuous prediction?

Which of the following is an example of continuous prediction?

• A. Spam detection
• B. Weather forecasting
• C. Customer segmentation
• D. Fault detection in social media

Answer: (B)

Weather forecasting is an example of continuous prediction because it involves estimating a range of potential future values, such as temperature, humidity, or precipitation levels, over time. Continuous prediction refers to predicting outcomes that can take any value within a continuous range rather than discrete categories. In weather forecasting, the models generate predicted values based on a series of factors, and the results are often expressed as specific measurements, like temperatures for upcoming days, which may be 75°F, 68°F, etc. This contrasts with discrete predictions, where the output would belong to specific categories, such as "spam" or "not spam" in spam detection, which is based on classifying inputs rather than predicting a range. The nature of weather phenomena requires a nuanced understanding of various variables that influence outcomes, making continuous prediction particularly suitable in this context.

Weather forecasting is an example of continuous prediction because it involves estimating a range of potential future values, such as temperature, humidity, or precipitation levels, over time. Continuous prediction refers to predicting outcomes that can take any value within a continuous range rather than discrete categories.

In weather forecasting, the models generate predicted values based on a series of factors, and the results are often expressed as specific measurements, like temperatures for upcoming days, which may be 75°F, 68°F, etc. This contrasts with discrete predictions, where the output would belong to specific categories, such as "spam" or "not spam" in spam detection, which is based on classifying inputs rather than predicting a range. The nature of weather phenomena requires a nuanced understanding of various variables that influence outcomes, making continuous prediction particularly suitable in this context.