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Introduction of Evaluation
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    1. A Confusion Matrix is a technique using a chart or table for summarising the performance of a classification based AI model by listing the predicted values of an AI model and the actual/correct outcome values.
    2. In True Positive(TP), both predicted value of the AI model and actual value are positive.
    3. In True Negative(TN), both predicted value of the AI model and actual value are negative.
    4. In False Positive(FP),the predicted value of the AI model is positive but actual value is negative.
    5. In False negative(FN), the predicted value of the AI model is negative but actual value is positive.
    6. Accuracy rate is the percentege of times the predictions out of all the observations are correct.
    7. Precision rateis the rate at which the desirable predictions turn out to be correct(True Positive out of all positive)
    8. Recall is a rate of correct predictions to the overall number of positive instances in the dataset.
    9. F1 Scoreis a measure of balance between precision and recall.




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Ch-8 EVALUATION


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Chapter based Question and Answer.

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Question With Answer of Ch-8 Evaluation Set-1

Question With Answer of Ch-8 Evaluation Set-2

Practice Question of Confusion Matrix

Competency based Questions -- Evaluation

1.An AI model has been developed to filter spam mails.In the detection of spam mail,it is okey if any spam mail remains undetected(false negative), but what if + miss any critical mail because it is classified as spam(false positive). In this situation, false Positive should be as low as possible.
Thus,here _______ is more vital as compared to recall.
  1. accuracy.
  2. F1 Score
  3. Precision
  4. Confusion Matrix
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Answer - (c) Precision


2.An AI model has been developed to detect credit card fraud detections. The aim is not to miss any fraud transactions. Therefore, we want False-Negative to be as low as possible.In these situations, we can compromise with the low precision, but ____ should be high. .
  1. accuracy
  2. recall
  3. F1 score
  4. confusion Matrix
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Answer-(b) recall