I refer to the paper by called Frustratingly Easy Domain Adaptation (http://www.umiacs.umd.edu/~hal/docs/daume07easyadapt.pdf) where the feature space of both the source and target data are augmented and used as input to a standard learning algorithm. The code is just 10 lines but in perl. I want to port to python but don't understand what the input data looks like that must be processed. http://hal3.name/easyadapt.pl.gz



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The input data are the files that you will read (those files will contain the lines of text).

Please refer to this link for more details on the code:


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