DAML

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• DAML This is the original implementation of the paper /Improving Domain-Adapted Sentiment Classification by Deep Adversarial Mutual Learning/ publicized in AAAI-2020.

** Requirement Python3.7 *** Python packages

• Tensorflow 1.14
• colored
• tqdm *** Other
• figlet (install from your system package manager, e.g. apt in Ubuntu or brew in MacOS)

** Guide *** How to run To run the naive baseline, just run #+BEGIN_SRC python train_naive.py --dataset SOURCE_DOMAIN --unlabeled_dataset TARGET_DOMAIN #+END_SRC

To run any other model, just run #+BEGIN_SRC python adv_train.py --model MODEL --dataset SOURCE_DOMAIN --unlabeled_dataset TARGET_DOMAIN #+END_SRC

*** Dataset If the datasets are not downloaded automatically through git clone, please check the following link to get the dataset and the word embedding: - [[https://drive.google.com/file/d/1Pd05BvEkyT0fXy-IcFO5n4rsY4qei8l6/view?usp=sharing]] - [[https://drive.google.com/file/d/1UdMPBUjRRm4npeKKnMuVfRdzXOyS7Z0N/view?usp=sharing]]

*** Available models The following model names are available, just as filenames show: | dann | adversarial cross-domain training framerwork without Mutual Learning | | sml | standard Mutual Learning framework | | ml | the proposed Mutual Learning framework | | ml3 | the proposed Mutual Learning framework with 3 models involved | | ml4 | the proposed Mutual Learning framework with 4 models involved |

*** Available datasets The following dataset names are available, just as shown in directory data/: - imdb - yelp13 - elc (Amazon Electronics) - clt (Amazon Clothing) - cd (Amazon CD)