Add noise parameter to LabelEncoder

[amontanez24]

Problem Description

Most distributions used by GaussianCopula and CopulaGAN fit better to continuous variables. In order to optimize the fitting process we can add noise to the output of the LabelEncoder to makes the transformed categorical variables continuous.

Expected behavior

• Add a new boolean parameter, add_noise, to __init__ for LabelEncoder.
  • If value is false, no changes should be made
  • If value is true, then
    • On the forward transform: Perform the label encoding as usual, and then add uniform noise within the interval. For example:
      1. Label=1 is noised to anything in the interval [1, 2) → 1.002, 1.3, 1.9999, ..
      2. Label=2 is noised to anything in the interval [2, 3)
      3. Label=3 is noised to anything in the interval [3, 4)
    • On the reverse transform floor the values to the nearest integer (eg. 3.9 becomes 3, 4.321 becomes 4) and then continue the normal reverse transformation.