Q:

Decision Tree for Choosing Most Likely Option?

I'm trying to find the right ML algorithm. Let's say I have three data columns. I have a binary outcome for each column (either the data column belongs to (Group A) classification or it does not), BUT in each set of three data columns that I feed in, exactly ONE and only one column belongs to Group A.
Which algorithm can I choose to select the ONE BEST result of the three each time? Can I do this with a decision tree?

A:

Decision tree aka ID3, can be suitable for this simple problem... best way is to check it on the data and see it's output prediction
ID3 have a problem of over fitting though 
basically every classifier can do a good job on this task, if it linearly separable even SVM can be a good choice, also I'm suggesting trying basic neural network with 1/2 nodes at the output layer for classification of 2 groups 
all of them are implemented via various packages and are fairly easy to use (almost any coding language)  

