Decision tree and RapidMiner performance measures - how to understand them
I would like to ask for help in the following matter.
In a decision tree created with gain ratio I just receive the classification of every instance to some class. In my case, one of 2 classes.
I do not understand how the RMSE is calculated if this measure is based on the difference between actual value and predicted value. If my classes use index symbols 0 and 1, does it mean that always the difference is 0 or 1 between actual value and predicted value?
Similarly, I do not undestand the margin definition. The margin is defined as the minimal confidence for the correct label. Should I calculate confidence for all the nodes and take the minimum value?
Finally, I do not understand the soft margin.Soft margin loss is the average soft margin loss on a classifier defined as the average of all 1- confidences for the correct label. How do I caculate 1-confidence for the correct label?