Question

Assuming a total sample of 1079 persons, among which 520 persons are having autism and 559 are healthy persons. When we pass the data of 520 autism patients into the KNN classifier, it correctly predicted “220” patients as autism category and the remaining patients into healthy category. Similarly, from 559 healthy persons, the KNN categorize “100” as autism patients and the remaining as healthy persons.

In the above scenario, if “autism” is considered as “positive class” and “healthy person” is considered as negative class then find the:

1. True Positive
2. True Negative
3. False Positive
4. False Negative
5. Sensitivity (True positive rate)
6. Specificity (True negative rate)
7. Accuracy
8. Precision
9. Draw the confusion matrix                               

Answer 1

Total samples overall = 1079

Postive (autism) samples having autism = 520

negative sample of (Healthy person) = 559

i) Confusion Matrix

False True

False 459   100

True 300 220

a) True positive (actual postive and predictèd positive) = 220

b) Ture negative(Actual negative and predicted negative) = 459

c) False positive (Actual negative and predicted positive) = 100

d) False negative (Actual positive and predicted negative) = 300

e) Sensitivity = (True positive)/(True postive + False negative) = 220/520 = 0.423

f) Specificity = (True negative)/(True negative + False positive) = 459/559 = 0.821

g) Accuracy = (True positive + Ture negative)/(True positive + Ture negative+False positive + False negative )

=(220+459)/(520+559) = 0.629

h) Precision = (True postive)/(True postive + False positive) =220/(220+100) = 220/320 = 0.6875