Interpretability for Industry 4.0 : Statistical and Machine Learning Approaches
Author | : Antonio Lepore |
Publisher | : Springer Nature |
Total Pages | : 130 |
Release | : 2022-10-19 |
ISBN-10 | : 9783031124020 |
ISBN-13 | : 3031124022 |
Rating | : 4/5 (022 Downloads) |
Download or read book Interpretability for Industry 4.0 : Statistical and Machine Learning Approaches written by Antonio Lepore and published by Springer Nature. This book was released on 2022-10-19 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides readers with a compact, stimulating and multifaceted introduction to interpretability, a key issue for developing insightful statistical and machine learning approaches as well as for communicating modelling results in business and industry. Different views in the context of Industry 4.0 are offered in connection with the concepts of explainability of machine learning tools, generalizability of model outputs and sensitivity analysis. Moreover, the book explores the integration of Artificial Intelligence and robust analysis of variance for big data mining and monitoring in Additive Manufacturing, and sheds new light on interpretability via random forests and flexible generalized additive models together with related software resources and real-world examples.