You create a binary classification model.
You need to evaluate the model performance.
Which two metrics can you use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
A . relative absolute error
B . precision
C . accuracy
D . mean absolute error
E . coefficient of determination
Answer: B,C
Explanation:
The evaluation metrics available for binary classification models are: Accuracy, Precision, Recall, F1 Score, and AUC.
Note: A very natural question is: ‘Out of the individuals whom the model, how many were classified correctly (TP)?’
This question can be answered by looking at the Precision of the model, which is the proportion of positives that are classified correctly.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance