User Manual

ASUS, Inc

 As mentioned above, we can use TP, TN, FP and FN values to calculate accuracy,

recall, loss, detection and overkill:

1. Accuracy = (TP+TN) / (TP+FP+FN+TN)

Accuracy is the ratio of total sum of all true events predicted over total

sum of all predicted events.

2. Precision = TP / (TP+FP)

Precision is the ratio of true positive events predicted over total sum of all

predicted positive events.

3. Recall = TP / (TP+FN)

Recall is the ratio of true positive events predicted over total sum of actual

positive events.

4. Loss = FN / (TP+FN)

Loss is the ratio of FN events over total sum of actual positive events.

5. Detection = TP / (TP+FN)

Detection is equal to Recall.

6. Overkill = FP / (FP+TN)

Overkill is the ratio of false positive events over sum of total actual

negative events.

Examples of Confusion Matrix

 Let's say, there are a batch of examinees total of 100 pcs. The true event is that

92 are good and 8 are no-good with defect.

 The examination event is as below:

1. 5pcs examined with defects, and they are defect parts (True Positive)

2. 90pcs examined good, and they are actually good parts (True Negative)

3. 3pcs examined with defects, and they are actually good parts (False

Positive)

4. 2pcs examined good, and they are defect parts (False Negative)"