Pardon my understanding of SVMs as it is very little.
We often hear of ensemble classifiers and stuff like this.
Say if i were to have 3 different SVM Models for the same dataset predicting a feature.
A test data point might have these results Model A: Class 1 Model B: Class 2 Model C: Class 3
However, how would i know which class label should be the correct one given a test data point? It is often talked about that each Model will assign a score to its result and the Class label with the highest score would be the one chosen.
However, as far as i understand, SVM output would be a result of either
1 or -1. A binary SVM so as to say. Pardon my weak explanation of the question as i am not too sure how should i be asking it.
My Focus would be to ask how does an SVM model even assign a score to its prediction