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This book is about a new field in statistical machine learning - about interpretation and explanation of predictive models. Machine learning models are widely used in predictive modelling, both for regression and classification.
This book is about a new field in statistical machine learning - about interpretation and explanation of predictive models. Machine learning models are widely used in predictive modelling, both for regression and classification.
Przemyslaw Biecek is a professor in human-oriented machine learning at the Warsaw University of Technology and Principal Data Scientist in Samsung R&D Institute Poland. His main research project is DrWhy.AI - tools and methods for exploration, explanation, visualisation, and debugging of predictive models.
Tomasz Burzykowski is professor of biostatistics at Hasselt University and Vice-President for Research at International Drug Development Institute (IDDI). He has published extensively on applications of statistics in medicine and biology.
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.
| Erscheinungsjahr: | 2021 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Seiten: | 324 |
| Inhalt: | Einband - fest (Hardcover) |
| ISBN-13: | 9780367135591 |
| ISBN-10: | 0367135590 |
| Sprache: | Englisch |
| Einband: | Gebunden |
| Autor: |
Biecek, Przemyslaw
Burzykowski, Tomasz |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 159 x 243 x 22 mm |
| Von/Mit: | Przemyslaw Biecek (u. a.) |
| Erscheinungsdatum: | 18.03.2021 |
| Gewicht: | 0,636 kg |
Przemyslaw Biecek is a professor in human-oriented machine learning at the Warsaw University of Technology and Principal Data Scientist in Samsung R&D Institute Poland. His main research project is DrWhy.AI - tools and methods for exploration, explanation, visualisation, and debugging of predictive models.
Tomasz Burzykowski is professor of biostatistics at Hasselt University and Vice-President for Research at International Drug Development Institute (IDDI). He has published extensively on applications of statistics in medicine and biology.
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.
| Erscheinungsjahr: | 2021 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Seiten: | 324 |
| Inhalt: | Einband - fest (Hardcover) |
| ISBN-13: | 9780367135591 |
| ISBN-10: | 0367135590 |
| Sprache: | Englisch |
| Einband: | Gebunden |
| Autor: |
Biecek, Przemyslaw
Burzykowski, Tomasz |
| Hersteller: | Taylor & Francis Ltd |
| Maße: | 159 x 243 x 22 mm |
| Von/Mit: | Przemyslaw Biecek (u. a.) |
| Erscheinungsdatum: | 18.03.2021 |
| Gewicht: | 0,636 kg |
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