I have a historical data that has discrete variables. Let say I have data points with class labels
1, 2, 3, 4, and 5
For a given classification problem, I can use the training data and then get the trained model. Using the trained model, I can classify the labels. However, I am also interested in prediction of class labels.
My requirement is that for a given $N$ points, lets say 5 data points, I want to know what is the probability that class label 5 more likely or less likely occurs from 0 to 1. Can anyone give me any ideas on this? For example my output will be a prediction probability for 5 instances, being:
0, 0.1, 0.2, 0.3, 0.5.
This means that the first data point has zero probability for class label 5 to occur. The 5th data point has the highest probability to occur around 50%. Can anyone give me idea on how to go about this problem?