AmirhosseinHonardoust/Missing-Data-Doctor
Missing Data Doctor is a diagnostic and treatment toolkit for missing values in machine learning datasets. It profiles missingness patterns, visualizes gaps, applies multiple imputation strategies, and evaluates their impact on model performance. Includes automated plots, metrics, and a full HTML report.
Effectively managing missing data is crucial for reliable machine learning models. This toolkit helps data scientists diagnose missing data patterns, understand which features are most affected, and visualize where the gaps are. It takes a raw dataset with missing values and produces a comprehensive HTML report, charts, and metrics comparing how different imputation strategies impact your model's performance.
Use this if you are a data scientist working with tabular datasets and need to understand, impute, and evaluate the impact of missing values on your predictive models.
Not ideal if you need to process streaming data or very large datasets that don't fit into memory, or if you require highly specialized, domain-specific imputation methods not covered by common strategies.
Stars
20
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Language
Python
License
MIT
Category
Last pushed
Nov 15, 2025
Commits (30d)
0
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