#20 Machine Learning & Data Science Challenge 20

#20 Machine Learning & Data Science Challenge 20

What is Accuracy and Misclassification Rate?

Accuracy:

  • Accuracy is defined as the ratio of the sum of True Positive and True Negative by Total(TP+TN+FP+FN).

$$Accuracy = TP + TN / TP + TN + FP + FN$$

  • However, there are problems with accuracy. It assumes equal costs for both kinds of errors. A 99% accuracy can be excellent, good, mediocre, poor, or terrible depending on the problem.

Misclassification Rate:

  • The misclassification Rate is defined as the ratio of the sum of False Positive and False Negative by Total(TP+TN+FP+FN).

  • The misclassification Rate is also called Error Rate.