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Multiple Imputation using Denoising Autoencoders

Project description

MIDAS2

Implementation of MIDAS in PyTorch. See Lall and Robinson (2022) for the original paper.

In addition to migrating to torch, this new version adds the following functionality:

  • Models can be fit on X and used to impute on new data X'
  • Automatic detection of column-types

Example usage

MIDAS2 follows the sklearn API, with fit and transform methods of an imputer object.

from midas2 import MIDAS

# Create a MIDAS model
mod = MIDAS()

# Fit the model to data
mod.fit(X, epochs = 10)

# Multiply impute missing data
X_imputed = mod.transform(m = 10)

CHANGELOG

  • Alpha release including combination rules function (26/06/2025)
  • Renamed the main module from 'MIDAS2' to 'model' (19/12/2024)
  • Restructured the package for easier install (19/12/2024)

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