The misclassification table is not present when the splitting method is class probability.
In the weighted case, the weighted count is the sum of the weights for a category. When you have weights, use the weighted counts to calculate the different weights.
In the weighted case, use weighted counts in place of counts.
The calculation of cost depends on whether the response variable is binary or multinomial.
Cost = (% Error × Input misclassification cost for class) / 100
The following equation gives the cost for the event class:
The following equation gives the cost for the non-event class:
The following equation gives the overall cost for all classes:
The following equation gives the overall cost for the multinomial case:
For example, consider a response variable with 3 classes and the following misclassification costs:
Predicted Class | |||
Actual class | 1 | 2 | 3 |
1 | 0.0 | 4.1 | 3.2 |
2 | 5.6 | 0.0 | 1.1 |
3 | 0.4 | 0.9 | 0.0 |
Then, consider that the following table gives the error percentages:
Predicted Class | |||
Actual class | 1 | 2 | 3 |
1 | N/A | 1% | 0.5% |
2 | 1.4% | N/A | 2.1% |
3 | 5% | 1.2% | N/A |
Finally, consider that the classes of the response variable have the following prior probabilities:
The following equation gives the overall cost: