is multi-label clasification for text only
Of course it can be done with numbers. After all, the text itself is converted to numbers to be classified. But you should not use regression for that. It is clearly a case for classification.
A regular classifier (for example, a neural network) usually has multiple outputs, one for each class. Each output returns the probability that the input vector belongs to that particular class.
In standard classification, you assign it to the class with the maximum probability. In your case, just assign it to all the classes for which p > 0.5 (assuming that the output is in [0, 1].
Regarding the question of whether your problem is a multi-regression or multi-classification problem, you can't know that just by looking at the inputs. You decide it based on what you are trying to find. Choose regression if you are trying to find numeric values in a continuous range (for example, predict the price and number of sales for a given product). Choose classification if you have a number of attributes that the input has or doesn't have.
I was working on a numeric dataset and apparently it is a multi variable output regression. I wanted to know if you can have a multi-label classification in a numeric dataset or it is strictly for text based.
For Eg: Stackoverflow an categorize every text/code into multiple tags like python,flask, python2.7 ... But can something like that be done with numbers. Sorry I know that this is a noob question but I wanted to know the answer. Thanks in Advance.