Datasets
Iris
Flower measurements for a compact, interpretable multiclass baseline and leakage audit.
Listing reviewed · source terms apply
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Research, software, data and methods. Inspect the context, compare your options, and take a useful next step.
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Methods
3.1. Cross-validation: evaluating estimator performance
A guide to model-evaluation splits, including grouped and time-series data, nested model selection and permutation-based assessment.
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Methods
1.13. Feature selection
A guide to variance filters, univariate tests, recursive elimination, model-based selection and selection inside pipelines.
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Methods
1.16. Probability calibration
A probability-calibration guide covering reliability curves and sigmoid, isotonic and temperature-scaling approaches.
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Methods
2.7. Novelty and Outlier Detection
A guide distinguishing outlier detection from novelty detection and comparing assumptions of several anomaly-detection methods.
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Datasets
2D elastodynamic metamaterials
Pixelated metamaterial unit-cell designs and band-gap locations and widths for investigating simulation surrogate reliability.
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Methods
3.4. Metrics and scoring: quantifying the quality of predictions
A broad scoring reference that distinguishes classification, regression, ranking and clustering metrics and their scorer interfaces.
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Datasets
3W dataset
Oil-production process signals for studying event detection across operating scenarios.
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Methods
5.1. Partial Dependence and Individual Conditional Expectation plots
A guide to partial-dependence and individual-conditional-expectation curves, including definitions, computation and correlated-input caveats.
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Methods
5.2. Permutation feature importance
A model-inspection guide explaining permutation importance and its limitations when predictors are strongly correlated.
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External articles
[Re] Badder Seeds: Reproducing the Evaluation of Lexical Methods for Bias Measurement
A replication examining lexical methods for measuring bias and sensitivity to seed choices.
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External articles
[Re] BiRT: Bio-inspired Replay in Vision Transformers for Continual Learning
A replication of replay-based continual learning with vision transformers, relevant to evaluating retention across sequential tasks.
Listing reviewed · source terms apply
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