evaluation other qs

Question 1

What is True Positive

Answer 1

The predicted value matches the actual value
The actual value was positive and the model predicted a positive value

Question 2

What is True Negative?

Answer 2

The predicted value matches the actual value
The actual value was negative and the model predicted a negative value

Question 3

What is False Positive?

Answer 3

The predicted value was falsely predicted
The actual value was negative but the model predicted a positive value
Also known as the Type 1 error

Question 4

What is False Negative?

Answer 4

The predicted value was falsely predicted
The actual value was positive but the model predicted a negative value
Also known as the Type 2 error

Question 5

What is Accuracy?

Answer 5

Accuracy is defined as the percentage of correct predictions out of all theobservations.

Question 6

What is Precision?

Answer 6

Precision is defined as the percentage of true positive cases versus all the caseswhere the prediction is true.

Question 7

What are the possible reasons for an AI model not being efficient?

Answer 7

• lack of training
• wrong data
• wrong algorithm
• not easy
• less accuracy