Hello babaluma

For others: Here is the link to the mentioned sf-thread:

click.

Regarding your problem:

I understand Platt Scaling this way:

**input**: the ExampleSet the original model was created with and the created model

**output: ** the "corrected" model.

Applying the corrected model to your test set results in real probabilities in the confidence column, i.e. confidence(c)=p(y=c|x=current Example).

hope this was helpful

Steffen

PS: This topic is really interesting. Recently I stumbled upon a paper converting scores of multiple-class-classifiers, but unfortunately, I did not have the time to study it yet. Here is the link (PDF):

Transforming Classifier Scores into Accurate Multiclass Probability Estimates