CYBER_CRIME_CONFUSION_MATRIX (5)

Confusion Matrix —

  • Positive(P): The predicted result is Positive (Example: Image is a cat)
  • Negative(N): the predicted result is Negative (Example: Images is not a cat)
  • True Positive(TP): Here TP basically indicates the predicted and the actual values is 1(True)
  • True Negative(TN): Here TN indicates the predicted and the actual value is 0(False)

Accuracy and Components of Confusion Matrix

An Overview of False Positives and False Negatives

What Are False Positives?

What Are False Negatives?

Strengthening Your Cybersecurity Posture

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