Différences entre versions de « Utilisateur:Arbg0002/brouillons/réseaux de neurones »

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** Zscore normalization: input variable data is converted into zero mean and unit variance
 
** Zscore normalization: input variable data is converted into zero mean and unit variance
 
** Sigmoidal normalization: nonlinear transformation of the input data into the range [-1,1], with a sigmoid function
 
** Sigmoidal normalization: nonlinear transformation of the input data into the range [-1,1], with a sigmoid function
 +
** Other normalization: e.g. if a variable is exponentially distributed, take the logarithm
 
* Data analysis
 
* Data analysis
 
* Validation of results
 
* Validation of results

Version du 12 avril 2019 à 11:10

Neural networks

Pre-processing

  • Data exploration (clean-up)
  • Data transformation
  • Outlier detection and removal
  • Data normalization, one of:
    • Min-Max normalization: linear scaling into a data range, typically [0,1]
    • Zscore normalization: input variable data is converted into zero mean and unit variance
    • Sigmoidal normalization: nonlinear transformation of the input data into the range [-1,1], with a sigmoid function
    • Other normalization: e.g. if a variable is exponentially distributed, take the logarithm
  • Data analysis
  • Validation of results