Fast multiple imputation using Random Forests and LightGBM, implementing Multiple Imputation by Chained Equations (MICE). Current version: 6.0.5, release cadence: irregular major versions with breaking changes.
pip install miceforestNo compatibility data collected yet for this library.
Verified import paths — ran on the pinned version, not inferred.
Basic imputation using the main class.
Pass a pandas DataFrame instead of a numpy array.
Use e.g., kernel = ImputationKernel(..., mean_match_strategy='shap', mean_match_candidates=10)
Use 'ImputationKernel' and 'ImputedData' from miceforest.
If loading a kernel saved with v5.x, re-run imputation on the original data instead of loading.
Use 'ImputedData' instead: from miceforest import ImputedData
Use 'data_subset' parameter instead, or adjust your code to v6.x API.