Przemyslaw Biecek, Tomasz Burzykowski (Belgium Hasselt University)

Explanatory Model Analysis

Explore, Explain, and Examine Predictive Models

• Broschiertes Buch

Produktbeschreibung

This book is about a new field in statistical machine learning â about interpretation and explanation of predictive models. Machine learning models are widely used in predictive modelling, both for regression and classification.

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Produktdetails

• Chapman & Hall/CRC Data Science Series
• Verlag: Taylor & Francis Ltd
• Seitenzahl: 324
• Erscheinungstermin: 26. September 2022
• Englisch
• Abmessung: 234mm x 156mm x 18mm
• Gewicht: 538g
• ISBN-13: 9780367693923
• ISBN-10: 0367693925
• Artikelnr.: 65612355

Autorenporträt

Flipbook: https://betaandbit.github.io/RML_ES

Inhaltsangabe

I. Introduction 1. Introduction. 2. Model Development. 3. Do
it
yourself. 4. Datasets and models. II. Instance Level. 5. Introduction to Instance
level Exploration. 6. Break
down Plots for Additive Attributions. 7. Break
down Plots for Interactions. 8. Shapley Additive Explanations (SHAP) for Average Attributions. 9. Local Interpretable Model
agnostic Explanations (LIME). 10. Ceteris
paribus Profiles. 11. Ceteris
paribus Oscillations. 12. Local
diagnostics Plots. 13. Summary of Instance
level Exploration. III. Dataset Level. 14. Introduction to Dataset
level Exploration. 15. Model
performance Measures. 16. Variable
importance Measures. 17. Partial
dependence Profiles. 18. Local
dependence and Accumulated
dependence Profiles. 19. Residual Diagnostics Plots. 20. Summary of Model
level Exploration. IV. Use
cases. 21. FIFA 19.