I've this matrix confusion:
[9779 107]
[2227 148]
What is the accuracy of my model? My doubt is because the confusion matrix is calculated based on Test dataset so how can it evaluate the accuracy of my model?
Thanks!
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Sign up to join this communityA confusion matrix gives you the following:
[TP, FP]
[FN, TN]
where TP = 'true positives'; FP = 'false positives'; FN = 'false negatives'; TN = 'true negatives'.
You can read more here: http://www.dataschool.io/simple-guide-to-confusion-matrix-terminology/
By taking TP+TN and dividing by TP+FP+FN+TN, you can get the classification accuracy of your model. In your case, that means (9779+148)/(9779+107+2227+148) = about 81%
More details:
This type of confusion matrix is used for binary classification.
Assuming you have the elements 9779 = True Positive, 148 = True Negative, you can obtain the accuracy by adding the diagonal elements, then dividing by the sum of all the numbers within the matrix. So for your example:
(9779 + 148)/(9779 + 148 + 107 + 2227) = 0.80964..
Hence, Accuracy = 80.96%
More info: http://www.dataschool.io/simple-guide-to-confusion-matrix-terminology/