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
Xand used to impute on new dataX' - 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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