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Fig.5 Balance line before and after the signal correction

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Contents

  • 1. Structure of DBN
  • 2. Preparation and selection of data
    • 2.1. Input variables
    • 2.2. Output variables
    • 2.3. Initial data frame
      • 2.3.1. Deleting highly correlated variables
    • 2.4. Selection of the most important variables
  • 3. Experimental part.
    • 3.1. Building models
      • 3.1.1. Brief description of the "darch" package
      • 3.1.2. Building the DBN model. Parameters.
    • 3.2. Formation of training and testing samples.
      • 3.2.1. Balancing classes and pre-processing.
      • 3.2.2. Coding the target variable
    • 3.3. Training the model
      • 3.3.1. Pre-training
      • 3.3.2. Fine-tuning
    • 3.4. Testing the model. Мetrics.
      • 3.4.1. Decoding predictions.
      • 3.4.2. Improving the prediction results
        • Calibration
        • Smoothing with a Markov chain model
        • Correcting predicted signals on the theoretical balance curve
      • 3.4.3. Metrics
  • 4. Structure of the Expert Advisor
    • 4.1. Description of the Expert Advisor's operation
    • 4.2. Self-control. Self-training
  • Installation and launching
  • Ways and methods of improving qualitative indicators.
  • Conclusion



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