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3.1. Cross-validation: evaluating estimator performance scikit-learn documentation
A guide to model-evaluation splits, including grouped and time-series data, nested model selection and permutation-based assessment.
Investigate How much optimism arises when repeated observations from the same group are split across train and test?
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1.13. Feature selection scikit-learn documentation
A guide to variance filters, univariate tests, recursive elimination, model-based selection and selection inside pipelines.
Investigate How much apparent accuracy is introduced by selecting features before cross-validation on noise-only data?
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1.16. Probability calibration scikit-learn documentation
A probability-calibration guide covering reliability curves and sigmoid, isotonic and temperature-scaling approaches.
Investigate How do calibration methods trade off log loss and reliability when the calibration sample is small?
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2.7. Novelty and Outlier Detection scikit-learn documentation
A guide distinguishing outlier detection from novelty detection and comparing assumptions of several anomaly-detection methods.
Investigate How does training-set contamination alter detection rates at a fixed false-positive target?
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3.4. Metrics and scoring: quantifying the quality of predictions scikit-learn documentation
A broad scoring reference that distinguishes classification, regression, ranking and clustering metrics and their scorer interfaces.
Investigate Can a scoring implementation reproduce independently computed confusion-matrix and probability-loss examples, including undefined edge cases?
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5.1. Partial Dependence and Individual Conditional Expectation plots scikit-learn documentation
A guide to partial-dependence and individual-conditional-expectation curves, including definitions, computation and correlated-input caveats.
Investigate When features are correlated, how many evaluation points used by a response curve fall outside a declared support region?
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5.2. Permutation feature importance scikit-learn documentation
A model-inspection guide explaining permutation importance and its limitations when predictors are strongly correlated.
Investigate How does duplicating a predictive feature change individual permutation-importance scores while predictive accuracy stays comparable?
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Advanced Features CVXPY documentation
A guide to dual variables, transformations, problem arithmetic and canonical forms for convex optimization.
Investigate Do reported primal and dual variables satisfy independently computed feasibility and complementary-slackness checks on small convex problems?
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bootstrap SciPy documentation
The bootstrap reference explains percentile, basic and bias-corrected accelerated confidence intervals, paired resampling and computation controls.
Investigate How do interval coverage and width compare for a known skewed distribution at small sample sizes?
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Compressed Sparse Graph Routines (scipy.sparse.csgraph) SciPy documentation
A tutorial on algorithms for graphs represented as sparse matrices, illustrated through path finding.
Investigate Do sparse-graph path computations agree with exact enumeration on tiny weighted graphs containing disconnected components?
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differential_evolution SciPy documentation
A reference for population-based stochastic optimization with bounds, constraints, initialization, updating and random-state controls.
Investigate At equal objective-evaluation budgets, how often are known target values reached across independent initial populations?
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Disciplined Convex Programming CVXPY documentation
A guide to constructing optimization expressions with known signs and curvature under disciplined convex programming rules.
Investigate Can a small suite distinguish mathematically equivalent formulations that are accepted or rejected by the stated DCP rules?
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