ML4NLP2

Contents:

  • Readme File
  • Multi-Source Domain Adaptation for RUL Prediction of Rotating Machinery
  • unitn_ml4nlp2
  • src
    • dataset module
    • losses module
    • model module
    • results module
    • signal_processing module
    • utils module
ML4NLP2
  • src
  • View page source

src

  • dataset module
    • Bearingset
      • Bearingset.get_dataloader()
  • losses module
    • AdversarialLoss
      • AdversarialLoss.forward()
      • AdversarialLoss.get_adversarial_result()
    • BNM()
    • CORAL()
    • DAANLoss
      • DAANLoss.forward()
      • DAANLoss.get_local_adversarial_result()
      • DAANLoss.update_dynamic_factor()
    • Discriminator
      • Discriminator.forward()
    • LambdaScheduler
      • LambdaScheduler.lamb()
      • LambdaScheduler.step()
    • MMDLoss
      • MMDLoss.forward()
      • MMDLoss.gaussian_kernel()
      • MMDLoss.linear_mmd2()
    • ReverseLayerF
      • ReverseLayerF.backward()
      • ReverseLayerF.forward()
    • TransferLoss
      • TransferLoss.forward()
  • model module
    • FeaturesExtractor
      • FeaturesExtractor.forward()
    • Regressor
      • Regressor.forward()
    • TransferNet
      • TransferNet.epoch_based_processing()
      • TransferNet.forward()
      • TransferNet.get_parameters()
      • TransferNet.predict()
  • results module
    • compute_results()
    • compute_score()
    • forecast_hi_lr()
    • forecast_hi_prophet()
  • signal_processing module
    • get_mfcc()
  • utils module
    • download_dataset()
    • excerr()
    • printt()
    • process_dataset()
    • process_features()
    • process_sample()
    • set_environment()
    • to_parquet()
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