Analysis of the features of the sample preparation stage for a generative-adversarial neural network

Authors

  • Zakharov Alexander
  • Tatjana Selivyorstova

DOI:

https://doi.org/10.34185/1991-7848.itmm.2020.01.035

Keywords:

NEURAL NETWORKS, DATA MINING, DATA PREPARATION, DATASET, GENERATIVE-ADVERSARIAL NEURAL NETWORK, LATENT VARIABLES

Abstract

The authors propose a generalized description of the Data Preparation stage used in Data Mining for training neural networks. The general features of the process of sampling from the general population of data, extraction and generation of features are identified and described. The classification of the sample is given, and the idea is substantiated that the classical approaches to the data preparation stage in data mining are not applicable when preparing data for training and using the generative-adversarial neural network.

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Published

2020-03-25

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