Interpretable Artificial Intelligence Using Nonlinear Decision Trees

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Interpretable Artificial Intelligence Using Nonlinear Decision Trees

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Author : Yashesh Deepakkumar Dhebar
language : en
Publisher:
Release Date : 2020

Interpretable Artificial Intelligence Using Nonlinear Decision Trees written by Yashesh Deepakkumar Dhebar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Electronic dissertations categories.

The recent times have observed a massive application of artificial intelligence (AI) to automate tasks across various domains. The back-end mechanism with which automation occurs is generally black-box. Some of the popular black-box AI methods used to solve an automation task include decision trees (DT), support vector machines (SVM), artificial neural networks (ANN), etc. In the past several years, these black-box AI methods have shown promising performance and have been widely applied and researched across industries and academia. While the black-box AI models have been shown to achieve high performance, the inherent mechanism with which a decision is made is hard to comprehend. This lack of interpretability and transparency of black-box AI methods makes them less trustworthy. In addition to this, the black-box AI models lack in their ability to provide valuable insights regarding the task at hand. Following these limitations of black-box AI models, a natural research direction of developing interpretable and explainable AI models has emerged and has gained an active attention in the machine learning and AI community in the past three years. In this dissertation, we will be focusing on interpretable AI solutions which are being currently developed at the Computational Optimization and Innovation Laboratory (COIN Lab) at Michigan State University. We propose a nonlinear decision tree (NLDT) based framework to produce transparent AI solutions for automation tasks related to classification and control. The recent advancement in non-linear optimization enables us to efficiently derive interpretable AI solutions for various automation tasks. The interpretable and transparent AI models induced using customized optimization techniques show similar or better performance as compared to complex black-box AI models across most of the benchmarks. The results are promising and provide directions to launch future studies in developing efficient transparent AI models.

Smart Systems Engineering

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Author : Cihan H. Dagli
language : en
Publisher: American Society of Mechanical Engineers
Release Date : 2007

Smart Systems Engineering written by Cihan H. Dagli and has been published by American Society of Mechanical Engineers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.

Proceedings Of The Third Siam International Conference On Data Mining

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Author : Daniel Barbara
language : en
Publisher: Soc for Industrial & Applied Math
Release Date : 2003

Proceedings Of The Third Siam International Conference On Data Mining written by Daniel Barbara and has been published by Soc for Industrial & Applied Math this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.

We are very pleased to present the proceedings of the 2003 SIAM International Conference on Data Mining. The field of Data Mining has seen a tremendous increase of interest in recent months. Applications of Data Mining are mentioned often in the daily press, especially in the fields of security and forensics. Thus, these are exciting times for researchers and practitioners in the area. We hope that the research captured by these proceedings helps in advancing this important field.

Advanced Topics In Artificial Intelligence

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Author :
language : en
Publisher:
Release Date : 1999

Advanced Topics In Artificial Intelligence written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Artificial intelligence categories.

1995 Ieee Conference On Control Applications

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Author : IEEE Control Systems Society
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 1995

1995 Ieee Conference On Control Applications written by IEEE Control Systems Society and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Technology & Engineering categories.

Preliminary Papers Of The Fourth International Workshop On Artificial Intelligence And Statistics

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Author :
language : en
Publisher:
Release Date : 1993

Preliminary Papers Of The Fourth International Workshop On Artificial Intelligence And Statistics written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Artificial intelligence categories.

Explainable Artificial Intelligence An Introduction To Interpretable Machine Learning

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Author : Uday Kamath
language : en
Publisher: Springer Nature
Release Date : 2021-12-15

Explainable Artificial Intelligence An Introduction To Interpretable Machine Learning written by Uday Kamath and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-15 with Computers categories.

This book is written both for readers entering the field, and for practitioners with a background in AI and an interest in developing real-world applications. The book is a great resource for practitioners and researchers in both industry and academia, and the discussed case studies and associated material can serve as inspiration for a variety of projects and hands-on assignments in a classroom setting. I will certainly keep this book as a personal resource for the courses I teach, and strongly recommend it to my students. --Dr. Carlotta Domeniconi, Associate Professor, Computer Science Department, GMU This book offers a curriculum for introducing interpretability to machine learning at every stage. The authors provide compelling examples that a core teaching practice like leading interpretive discussions can be taught and learned by teachers and sustained effort. And what better way to strengthen the quality of AI and Machine learning outcomes. I hope that this book will become a primer for teachers, data Science educators, and ML developers, and together we practice the art of interpretive machine learning. --Anusha Dandapani, Chief Data and Analytics Officer, UNICC and Adjunct Faculty, NYU This is a wonderful book! I’m pleased that the next generation of scientists will finally be able to learn this important topic. This is the first book I’ve seen that has up-to-date and well-rounded coverage. Thank you to the authors! --Dr. Cynthia Rudin, Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, and Biostatistics & Bioinformatics Literature on Explainable AI has up until now been relatively scarce and featured mainly mainstream algorithms like SHAP and LIME. This book has closed this gap by providing an extremely broad review of various algorithms proposed in the scientific circles over the previous 5-10 years. This book is a great guide to anyone who is new to the field of XAI or is already familiar with the field and is willing to expand their knowledge. A comprehensive review of the state-of-the-art Explainable AI methods starting from visualization, interpretable methods, local and global explanations, time series methods, and finishing with deep learning provides an unparalleled source of information currently unavailable anywhere else. Additionally, notebooks with vivid examples are a great supplement that makes the book even more attractive for practitioners of any level. Overall, the authors provide readers with an enormous breadth of coverage without losing sight of practical aspects, which makes this book truly unique and a great addition to the library of any data scientist. Dr. Andrey Sharapov, Product Data Scientist, Explainable AI Expert and Speaker, Founder of Explainable AI-XAI Group

Artificial Neural Networks

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Author :
language : en
Publisher:
Release Date : 2002

Artificial Neural Networks written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Neural networks (Computer science) categories.

Library Information Science Abstracts

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Author :
language : en
Publisher:
Release Date : 2004

Library Information Science Abstracts written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Information science categories.

Mathematical Reviews

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Author :
language : en
Publisher:
Release Date : 2005

Mathematical Reviews written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Mathematics categories.