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 = 1079

Total positive (autism) = 520

Total negative (Healthy person) = 559

i) Confusion Matrix

	False	True
False	459	100
True	300	220

a) True positive (Actually postive and after test positive) = 220

b) Ture negative(Actually negative and after test negative) = 459

c) False positive (Actually negative and after test positive) = 100

d) False negative (Actually positive and after test 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