Confusion Matrix using scikit-learn in Python

Understanding True Positive, True Negative, False Positive and False Negative in a Confusion Matrix

True Positive (TP) 

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

True Negative (TN) 

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

False Positive (FP) – Type 1 error

• 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

False Negative (FN) – Type 2 error

• 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

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