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Explanatory Model Analysis: Explore, Explain, and Examine Predictive Models (Chapman & Hall/CRC Data Science Series)

Explanatory Model Analysis: Explore, Explain, and Examine Predictive Models (Chapman & Hall/CRC Data Science Series)

Explanatory Model Analysis: Explore, Explain, and Examine Predictive Models
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Explanatory Model Analysis: Explore, Explain, and Examine Predictive Models (Chapman & Hall/CRC Data Science Series) Hardback - 2021

by Biecek, Przemyslaw

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  • Title Explanatory Model Analysis: Explore, Explain, and Examine Predictive Models (Chapman & Hall/CRC Data Science Series)
  • Author Biecek, Przemyslaw
  • Binding Hardback
  • Condition Used - Good
  • Pages 324
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Publication date 2021-03-18
  • Bookseller's Inventory # 0367135590.G
  • ISBN 9780367135591 / 0367135590
  • Weight 0.7 lbs (0.32 kg)
  • Dimensions 8.9 x 5.9 x 0.8 in (22.61 x 14.99 x 2.03 cm)
  • Category Business / Economics / Finance
  • Quantity available 1

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Reader reviews for Explanatory Model Analysis: Explore, Explain, and Examine Predictive Models (Chapman & Hall/CRC Data Science Series)

From the publisher

Explanatory Model Analysis Explore, Explain and Examine Predictive Models is a set of methods and tools designed to build better predictive models and to monitor their behaviour in a changing environment. Today, the true bottleneck in predictive modelling is neither the lack of data, nor the lack of computational power, nor inadequate algorithms, nor the lack of flexible models. It is the lack of tools for model exploration (extraction of relationships learned by the model), model explanation (understanding the key factors influencing model decisions) and model examination (identification of model weaknesses and evaluation of model's performance). This book presents a collection of model agnostic methods that may be used for any black-box model together with real-world applications to classification and regression problems.

About the author

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.

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