Common Pitfalls and Recommended Practices

Common Pitfalls and Recommended Practices.

Type

Software

Intellectual base

Primary research

Link

https://scikit-learn.org/stable/common_pitfalls.html

Cited by

2 citations across 2 artifacts.

Each citation links to the sentence it supports in the citing article.

Mechanisms

• Feature Scaling and Normalization Pipeline
  • Data leakage is the classic trap: fitting the scaler on all available data, including what should have been held out for testing, lets information bleed backward and flatters every downstream evaluation

    This sourceDefines data leakage and shows that fitting normalization on test data contaminates evaluation and produces overly optimistic scores.

• Preprocessing Fit-on-Training-Only
  • The discipline that guards against it is to route all preprocessing through one enforced pipeline whose transforms fit only within the training partition,

    This sourceRecommends using a pipeline so preprocessing is applied consistently, fitted only on training data, and kept inside cross-validation and hyperparameter-tuning isolation.

Verification

Does it exist? Not checked yet. This entry carries no identifier to resolve. It was extracted from the citation as written in the article, normalized, and deduplicated against the rest of the registry.

Does it back the claim? Not recorded. Neither this nor any other of the 2 citations of this work carries a recorded support check.

Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.

See how references were verified.

Links previously used in the corpus

Before the registry existed this work was also linked 1 other way.

• https://scikit-learn.org/dev/common_pitfalls.html ×1

Registry ID ref:deae0dd35906 · see in the full table