An open library for your next question. Public pilot
Executable Science
Log inCreate account
THE OPEN LIBRARY

Find your next starting point.

Research, software, data and methods. Inspect the context, compare your options, and take a useful next step.

34 resources · Curated orderClear filters
Software

NumPy

Upstream project repository

Multidimensional array operations and numerical linear algebra for scientific Python.

Investigate How do sequential and pairwise array reductions behave on cancellation-heavy inputs?

Listing reviewed · source terms apply
Methods

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?

Listing reviewed · source terms apply
Methods

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?

Listing reviewed · source terms apply
Methods

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?

Listing reviewed · source terms apply
Methods

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?

Listing reviewed · source terms apply
Methods

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?

Listing reviewed · source terms apply
Methods

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?

Listing reviewed · source terms apply
Methods

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?

Listing reviewed · source terms apply
External articles

[Re] Curve-Fitting with Piecewise Parametric Cubics

ReScience C

A replication of piecewise parametric cubic curve fitting, useful for studying how a geometric approximation is constructed and checked.

Investigate Can the fitting procedure meet a fixed geometric error tolerance on evaluator-generated curves with different curvature?

Listing reviewed · source terms apply
External articles

[Re] Weighted Voronoi Stippling

ReScience

A replication of weighted Voronoi stippling, a geometric method for distributing sample points according to image intensity.

Investigate How closely do generated stipple densities match evaluator-defined synthetic intensity maps at fixed point counts?

Listing reviewed · source terms apply
Methods

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?

Listing reviewed · source terms apply

Recorded license evidence is scoped to each source; it is not a blanket permission or a verification result.