Question

To measure a predictive model's accuracy, you

A: Multiply the number of total predictions by the percentage of correct predictions
B: Divide the number of predictions by the total dataset
C: Measure the ratio of the model's error curve
D: Divide the number of correct predictions by the total number of predictions

Answer 1

To measure a predictive model's accuracy, divide the number of correct predictions by the total number of predictions, yielding the accuracy rate. Option b.

Step-by-step explanation:

To measure a predictive model's accuracy, the correct approach is option D: Divide the number of correct predictions by the total number of predictions.

This gives you the ratio of successful predictions to total predictions, which is also known as the accuracy rate. In other words, if a model made 80 correct predictions out of 100 total predictions, its accuracy would be 80/100 or 80%.

The process of measuring accuracy is essential in various fields, such as statistics, data science, and machine learning, where predictive modeling plays a crucial role. The accuracy rate helps provide an estimate of how well the predictive model will perform in practical applications, allowing for adjustments and improvements to enhance its efficacy.

So option B is correct.