Which metric should you review?

You are a data scientist creating a linear regression model.

You need to determine how closely the data fits the regression line.

Which metric should you review?
A . Coefficient of determination
B . Recall
C . Precision
D . Mean absolute error
E . Root Mean Square Error

Answer: A

Explanation:

Coefficient of determination, often referred to as R2, represents the predictive power of the model as a value between 0 and 1. Zero means the model is random (explains nothing); 1 means there is a perfect fit. However, caution should be used in interpreting R2 values, as low values can be entirely normal and high values can be suspect.

References: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-

reference/evaluate-model