pip install -r requirements.txt
python main.py -t
Note: You need to put the test.txt file in the folder Polynomial/
Note2: Since the predict() function (from the given starter code) accepts one expression at a time I havent been able to do batch processing during prediction, making it slower.
python train.py
Note: This will train the model on data from train.txt
Open Approach_explanation.pdf
to view a brief doc on my work.
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Model weights and language details are stored in
polynomial/weights
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network.txt
contains the printed network architecture for the best performing model. -
Extra model weights (for model 1, 2, 3 (described in Approach_explanation.pdf)) uploaded here just in case. Although a few other changes would need to be made to the code to run using these weights.