Missing Data Imputation ML Frameworks

Tools and frameworks for handling, imputing, and analyzing missing values in datasets across various modalities and domains. Does NOT include general data cleaning, time-series forecasting without imputation focus, or synthetic data generation unrelated to missingness mechanisms.

There are 27 missing data imputation frameworks tracked. 1 score above 70 (verified tier). The highest-rated is sktime/skpro at 84/100 with 314 stars and 41,366 monthly downloads.

Get all 27 projects as JSON

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#	Framework	Score	Tier	Stars	Language
1	sktime/skpro A unified framework for tabular probabilistic regression, time-to-event...	84	Verified	314	Python
2	WenjieDu/PyGrinder PyGrinder: a Python toolkit for grinding data beans into the incomplete for...	61	Established	65	Python
3	WenjieDu/Awesome_Imputation Awesome Deep Learning for Time-Series Imputation, including an unmissable...	54	Established	411	Python
4	ocbe-uio/imml A Python package for integrating, processing, and analyzing incomplete...	49	Emerging	24	Python
5	DoubleML/doubleml-for-r DoubleML - Double Machine Learning in R	48	Emerging	160	R
6	MIDASverse/rMIDAS R package for missing-data imputation with deep learning	48	Emerging	36	Python
7	vanderschaarlab/hyperimpute A framework for prototyping and benchmarking imputation methods	39	Emerging	196	Python
8	aangelopoulos/ltt Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control	39	Emerging	72	Jupyter Notebook
9	imputr/imputr Python library for easy and fast ML-based & conventional imputation techniques.	38	Emerging	32	Python
10	feruzoripov/tsgap Time-series missingness simulation separating mechanisms (MCAR/MAR/MNAR)...	37	Emerging	1	Python
11	SAP/knn-sampler Machine learning imputation method to recover the distribution of missing...	35	Emerging	9	Jupyter Notebook
12	haghish/mlim mlim: single and multiple imputation with automated machine learning	33	Emerging	32	R
13	TyMill/SynthPred A Julia package for synthetic data analysis, advanced imputation (ARIMA,...	29	Experimental	5	Julia
14	thibaultcordier/risk-control A toolkit to calibrate predictive algorithms to achieve risk control.	28	Experimental	6	Python
15	DoubleML/DoubleMLReplicationCode Replication of Simulations in Bach et al. (2024) - DoubleML - An...	26	Experimental	8	R
16	blind-contours/CVtreeMLE :deciduous_tree: :dart: Cross Validated Decision Trees with Targeted Maximum...	26	Experimental	6	R
17	Akchaykumar2004/Missing-Data-Doctor 🩺 Diagnose and treat missing values in machine learning datasets with tools...	22	Experimental	—	Python
18	AmirhosseinHonardoust/Missing-Data-Doctor Missing Data Doctor is a diagnostic and treatment toolkit for missing values...	21	Experimental	20	Python
19	miriamspsantos/heterogeneous-distance-functions A collection of heterogeneous distance functions handling missing values.	18	Experimental	7	MATLAB
20	missValTeam/Iscores Scoring rules for missing values imputations (Michel et al., 2021)	18	Experimental	7	R
21	liangyuanhu/Variable-selection-w-missing-data A general variable selection approach in the presence of missing data in...	17	Experimental	5	R
22	jannebor/dd_forecast Code for predicting probabilities of threat for Data Deficient species of...	17	Experimental	5	R
23	fchamroukhi/FLaMingos Functional Latent datA Models for clusterING heterogeneOus curveS	15	Experimental	6	R
24	miriamspsantos/synthetic-missing-data A library for synthetic missing data generation.	12	Experimental	4	MATLAB
25	kennethleungty/DataWig-Missing-Data-Imputation Imputation of Missing Data in Tables	12	Experimental	12	Jupyter Notebook
26	michelelagreca/Classification-On-Imputed-Data Project of the 'Data and Information Quality' Course, aiming on describing...	10	Experimental	1	Jupyter Notebook
27	marcvidalbadia/functional-whitening Online Material for Vidal and Aguilera (2022). Novel whitening approaches in...	10	Experimental	3	R