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

Topic Evauation
Type Short answer type
Class 10

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2 Answers

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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.


Study more about Evaluation at Evaluation Class 10

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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. 

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