I have created an experiment in azure machine learning studio, this experiment is multi-class classification problem using multi-class neural network algorithm, I have also add 'feature hashing' module to transform a stream of English text into a set of features represented as integers. I have successfully run the experiment but when i publish it as web service endpoint i got message "Reduce the total number of input and output columns to less than 1000 and try publishing again." I understood after some research that feature hashing convert text into thousands of feature but the problem is how i publish it as web service? and i don't want to remove 'feature hashing' module.
It sounds like you are trying to output all those thousands of columns as an output. What you really only need is the scored probability or the scored label. To solve this, just drop all the feature hashed columns from the score model module. To do this add in a project columns module, and tell it to start with "no columns" then "include" by "column names", and just add predicted column (scored probability/scored label).
Then hook up the output of that project columns module to your web service output module. Your web service should now be returning only 1-3 columns rather than thousands.