Page 329 - AI Ver 1.0 Class 10
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3. Explain in short the important terminologies of Confusion Matrix.
4. Give two reasons for the inefficiency of the AI Model.
B. Long answer type questions:
1. A Model made the following predictions. Calculate Accuracy, Precision, Recall and F1 Score.
Confusion Matrix Reality: 1 Reality: 0
Predicted: 1 100 85
Predicted: 0 80 32
2. In today’s Scenario, People receive constant mails from the organizations they are connected with and they have to be
classified into spam and non-spam as required. Now it has to be decided which mails to be categorized and set as spam
mails according to the mails received till date, The confusion matrix for the same is as follows:
Confusion Matrix Reality: 1 Reality: 0
Predicted: 1 40 24
Predicted: 0 10 36
Give an example for:
a. High False Negative cost
b. High False Positive cost
3. In the state there is a spread of dengue, and precautions are to be taken to stop the spread, so that medicine stocks can
be arranged, some actual cases have been detected and the frequency of the infections have been detected, following
predictions are being done, the confusion matrix for the same is as follows:
Confusion Matrix Reality: 1 Reality: 0
Predicted: 1 24 14
Predicted: 0 8 28
Why is F1 score considered the best of all the Evaluation methods?
4. Differentiate between True Positive and False Positive.
C. Activities:
1. COVID-19 is under control and schools have opened after a year long period. The government has asked for a consent
from the parents whether they want to send the child to the school or not. Though the consents numbers filled by
the parents are quite high still the number of students coming to school are sometimes low or average. The school
authorities plans to deploy an AI Model to predict the number of students coming to the school on daily basis,
Do the given task based on the above case study:
Evaluation 327

