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3. With the help of which of the following, Prediction and Reality can be easily mapped together?
a. Predictions b. Reality
c. Confusion Matrix d. Recall
4. What will be the outcome, if the Prediction is “Yes” and it matches with the Reality? and what will be the outcome, if the
Prediction is “Yes” and it does not match with the Reality?
a. True Negative, False Negative b. True Negative, False Positive
c. True Positive, False Positive d. True Positive, True Negative
5. Which of the following is not an example of an evaluation method?
a. Precision b. Accuracy
c. Prediction d. Recall
6. ………………………. is defined as the fraction of positive cases that are correctly identified.
a. Precision b. Accuracy
c. Recall d. F1 Score
7. F1 Score is 1 when:
a. Recall and Precision is 100% b. Recall is 100%
c. Precision d. Recall and Precision is 0
8. ………………………. is defined as the percentage of correct predictions out of all the observations. [CBSE Sample Paper, 2021]
a. Predictions b. Accuracy
c. Reality d. F1 Score
9. Recall-Evaluation method is: [CBSE Sample Paper, 2021]
a. defined as the fraction of positive cases that are correctly identified.
b. defined as the percentage of true positive cases versus all the cases where the prediction is true.
c. defined as the percentage of correct predictions out of all the observations.
d. comparison between the prediction and reality
10. In a confusion matrix handling data for a model predicting breast cancer, what does False Positive refer to?
a. Model predicted positive and the person has breast cancer in reality.
b. Model predicted positive and the person does not have breast cancer in reality.
c. Model predicted negative and the person has breast cancer in reality.
d. Model predicted negative and the person does not have breast cancer in reality.
B. Fill in the blanks.
1. ……….……................ is defined as the percentage of correct predictions out of all the observations.
2. False Positive means the predicted value was ……….……................ .
3. A model is said to have a good performance if the F1 Score for that model is ……….……................ .
4. ……….……................ is the measure of a test’s accuracy.
5. ……….……................ is the stage of testing the model.
320 Touchpad Artificial Intelligence-X

