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Classification of Tabular Data using High-Dimensional Mapping and Deep Learning Network

  • Journal of Internet of Things and Convergence
  • Abbr : JKIOTS
  • 2023, 9(6), pp.1-6
  • Publisher : The Korea Internet of Things Society
  • Research Area : Engineering > Computer Science > Internet Information Processing
  • Received : October 26, 2023
  • Accepted : November 24, 2023
  • Published : December 29, 2023

G. T. Kim 1 Won-Du Chang 2

1부경대학교 의생명기계전기융합공학
2부경대학교

Accredited

ABSTRACT

Deep learning has recently demonstrated conspicuous efficacy across diverse domains than traditional machine learning techniques, as the most popular approach for pattern recognition. The classification problems for tabular data, however, are remain for the area of traditional machine learning. This paper introduces a novel network module designed to tabular data into high-dimensional tensors. The module is integrated into conventional deep learning networks and subsequently applied to the classification of structured data. The proposed method undergoes training and validation on four datasets, culminating in an average accuracy of 90.22%. Notably, this performance surpasses that of the contemporary deep learning model, TabNet, by 2.55%p. The proposed approach acquires significance by virtue of its capacity to harness diverse network architectures, renowned for their superior performance in the domain of computer vision, for the analysis of tabular data.

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