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Implementation of manuscript 'Overcoming Negative Transfer by Online Selection: Distant Domain Adaptation for Fault Diagnosis'

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OSAA

This is the PyTorch implementation of manuscript 'Overcoming Negative Transfer by Online Selection: Distant Domain Adaptation for Fault Diagnosis'

Architecture of OSAA

image

Packages to be installed

pip install torch
pip install torchvision
pip install matplotlib
pip install seaborn
pip install pandas
pip install scorch
pip install wandb -U
pip install openpyxl

Training

cd OSAA
mkdir PU
mkdir CWRU

Download from https://drive.google.com/file/d/1a0StnzWNabPyVAUMPax-R3mEYlPUXkS9/view?usp=sharing and put them into folder PU (parallel to main.py)

Download from https://drive.google.com/file/d/1Urp5AzZi79hs-u0_wJOIlQHvB070q6Ag/view?usp=sharing and put them into folder CWRU

Training

  • Open main.py to check for training potions in the parser
  • Look for more configurations in folder config
  • Run the following command:
python main.py

An example is

python main.py --dataset PU --experiment_description test

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Implementation of manuscript 'Overcoming Negative Transfer by Online Selection: Distant Domain Adaptation for Fault Diagnosis'

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