Question

What are True Positive and False Positive situations in the confusion matrix regarding an AI model?

Topic	Evauation
Type	Short answer type
Class	10

Answer 1

True Positive (TP)- The predicted value matches the actual value, i.e., the actual value was positive and the model predicted a positive value.

False Positive (FP)-The predicted value was falsely predicted, i.e., the actual value was negative but the model predicted a positive value. It is also known as Type1 error.

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Study more about Evaluation at Evaluation Class 10

Answer 2

Confusion matrix visualization. True positive (TP): Observation is predicted positive and is actually positive. False positive (FP): Observation is predicted positive and is actually negative. True negative (TN): Observation is predicted negative and is actually negative.