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This code is the companion to "Using Domain Adaptaion to Improve the Modeling of Water Quality with Sparse Data" (copied from https://github.com/CC-Cheung/Master-Thesis)

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
Download		Download
Output		Output
viz		viz
.Rhistory		.Rhistory
README.md		README.md
data_processing.py		data_processing.py
invariant.py		invariant.py
requirements.txt		requirements.txt
results_analysis.py		results_analysis.py
variant.py		variant.py

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Using Domain Adaptation to Improve the Modeling of Water Quality with Sparse Data

Requirements

pip install -r requirements.txt

Usage

Uncomment and desired lines of code.

Download xlsx files from HTLP dataset into Data/raw.
Use data_processing.py to create training data.
Use invariant.py to pretrain on source domain data.
Use Download/download.py to download relevant models.
Use variant.py to train fine-tune in the target domain.
Use Download/download.py to download results.
Use result_analysis.py to analyse the various metrics.
Use viz/viz_variant.py and viz/viz_invariant.py to make the graphs.

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This code is the companion to "Using Domain Adaptaion to Improve the Modeling of Water Quality with Sparse Data" (copied from https://github.com/CC-Cheung/Master-Thesis)

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