facebookresearch/balance — The balance python package offers a simple workflow and methods for dealing with biased data samples…

Description and use

The **balance** Python package provides a straightforward workflow for correcting sample bias, enabling reliable inference from biased datasets to a target population. It includes tools for estimating and applying weighting schemes, assessing balance diagnostics, and integrating bias‑adjustment steps into typical data‑analysis pipelines. Ideal for researchers and practitioners who need to mitigate selection bias in their statistical or machine‑learning models.

Problem

facebookresearch/balance helps remove repetitive manual operations from a workflow.

Outcome

Early or unclear: treat as research material until maintenance, releases, docs, and issue activity are verified.

Workflow

• remove manual work
• connect tools into repeatable flows
• schedule operational tasks

Evidence

The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to some target population of interest.

Source