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When scikit‑learn’s estimator.fit() throws a ValueError about inconsistent sample counts, the culprit is often hidden alignment bugs. This guide walks you through the most common causes, how to check them, and fixes that keep your data honest.
Manual scaling and encoding outside your model invites data leakage. A ColumnTransformer inside a Pipeline keeps numeric and categorical preprocessing consistent from training through prediction.
An architecture note that outlines the requirements, minimal design, trust boundaries, operational checks, and failure conditions for a leakage‑free preprocessing pipeline in supervised learning.
Learn how to combine numeric and categorical preprocessing into a single Pipeline to avoid data leakage and simplify model training.
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