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name: decomposition description: "Routes scikit-plot PCA visualization requests for component-variance and 2-D projection plots." disable-model-invocation: true metadata: disco-role: operating license: MIT

Decomposition

Use this sub-skill for the scikitplot.decomposition PCA visualization functions. These routes expect a fitted PCA-like estimator and return Matplotlib Axes objects.

Route here

• Plot cumulative explained variance with plot_pca_component_variance.
• Plot a labeled 2-D PCA projection with plot_pca_2d_projection.
• Add biplot vectors and feature labels when the fitted estimator exposes component vectors.
• Validate the route quickly with scripts/decomposition_smoke.py.

Inputs to check first

1. Fit the PCA estimator before plotting.
2. For component variance, confirm the estimator has explained_variance_ratio_.
3. For 2-D projection, confirm the estimator has transform(X) and produces at least two coordinates.
4. For biplots, confirm components_[:2, :] exists and feature_labels, if supplied, align with input features.
5. Pass ax= when embedding into a figure layout.

Common decisions

• Use target_explained_variance to highlight the minimum component count that reaches a target cumulative ratio.
• Use cmap to choose class colors in projection plots.
• Use biplot=True only when feature vectors are meaningful and the plot will not be too crowded.
• Keep the PCA and data matrix in the same preprocessing space used during fit.

Reroute

• Metric curves or silhouette analysis: ../metrics/SKILL.md.
• Feature importances or learning curves: ../estimators/SKILL.md.
• Elbow curves for clusterers: ../clustering/SKILL.md.
• Legacy scikitplot.plotters calls to PCA helpers: ../legacy-factories/SKILL.md.

Read next

• references/api-reference.md for verified signatures and estimator requirements.
• references/workflows.md for component-variance and projection recipes.
• references/troubleshooting.md for unfitted PCA, missing attributes, biplot, and Axes errors.
• scripts/decomposition_smoke.py for a tiny Agg-backed PCA smoke run.