How to calculate proximity measure for symmetric binary attributes?
Contingency table for binary data:
Object 2 |
Object 1 |
|
1 / True / Positive |
0 / False / Negative |
Sum |
1 / True / Positive |
A |
B |
A + B |
0 / False / Negative |
C |
D |
C + D |
Sum |
A + C |
B + D |
|
Name |
Gender |
Job_Status |
Akram |
Male |
Regular |
Ali |
Male |
Contract |
Consider 1 for positive/True and 0 for negative/False
Here we are considering Male and regular as positive and female and contract as negative.
A = Akram is positive and Ali is also positive. so A=1 because Ali and Akram both are male and the male is positive.
B = Akram is positive and Ali is negative. So B=1 because Akram is regular that is positive and Ali is on contract that is negative
C = Akram is negative and Ali is 1. So C = 0 because Akram is never negative. He is male and regular. and male and regular both are positive.
D = Akram is negative and Ali is also negative. So D=0 because Akram is never negative. He is always positive(male and regular).
Next Similar Tutorials
- Proximity Measure for Nominal Attributes – Click Here
- Distance measure for asymmetric binary attributes – Click Here
- Distance measure for symmetric binary variables – Click Here
- Euclidean distance in data mining – Click Here Euclidean distance Excel file – Click Here
- Jaccard coefficient similarity measure for asymmetric binary variables – Click Here
- Cosine similarity in data mining – Click </a