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Interactive Quiz
Test your knowledge!
1
In binary classification, how is precision defined?
A
The number of correctly classified positive elements divided by the total number of actual positive elements
B
The number of correctly classified positive elements divided by the total number of elements classified as positive by the model
C
The number of correctly classified negative elements divided by the total number of actual negative elements
D
The total number of correct predictions divided by the total number of predictions
2
Which metric is defined as the harmonic mean between precision and recall?
A
Accuracy
B
F1-score
C
Specificity
D
Average Precision (AP)
3
What is the X-axis (abscissa) in the ROC curve?
A
The true positive rate (recall)
B
The false negative rate
C
The false positive rate (1 - specificity)
D
Precision
4
Which metric is the average of the squared errors between predicted and actual values?
A
Mean Absolute Error (MAE)
B
Mean Squared Error (MSE)
C
Intersection Over Union (IoU)
D
Log loss
5
In a segmentation task, which metric is more suitable than IoU to reduce bias toward small objects and rare classes?
A
Average Precision (AP)
B
Dice Coefficient
C
F1-score
D
Recall
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