1.1 - 8.10 - IDWT (ML Engine) - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Teradata Vantage
Release Number
October 2019
Content Type
Programming Reference
Publication ID
English (United States)

The IDWT function is the inverse of DWT (ML Engine); that is, IDWT applies inverse wavelet transforms on multiple sequences simultaneously. IDWT takes as input the output table and meta table output by DWT and outputs the sequences in time domain. (Because the IDWT output is comparable to the DWT input, the inverse transformation is also called the reconstruction.)

How Machine Learning Engine function IDWT works

This is a typical IDWT use case:

  1. Apply DWT to sequences to create their coefficients and corresponding metadata.
  2. Filter the coefficients by methods appropriate for the objects (for example, minimum threshold or top n coefficients).
  3. Apply IDWT to the filtered coefficients to reconstruct the sequences.
  4. Compare the reconstructed sequences to their original counterparts.