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Author: Igor Chikalov Publisher: Springer Science & Business Media ISBN: 3642226612 Category : Technology & Engineering Languages : en Pages : 108
Book Description
Decision tree is a widely used form of representing algorithms and knowledge. Compact data models and fast algorithms require optimization of tree complexity. This book is a research monograph on average time complexity of decision trees. It generalizes several known results and considers a number of new problems. The book contains exact and approximate algorithms for decision tree optimization, and bounds on minimum average time complexity of decision trees. Methods of combinatorics, probability theory and complexity theory are used in the proofs as well as concepts from various branches of discrete mathematics and computer science. The considered applications include the study of average depth of decision trees for Boolean functions from closed classes, the comparison of results of the performance of greedy heuristics for average depth minimization with optimal decision trees constructed by dynamic programming algorithm, and optimization of decision trees for the corner point recognition problem from computer vision. The book can be interesting for researchers working on time complexity of algorithms and specialists in test theory, rough set theory, logical analysis of data and machine learning.
Author: Igor Chikalov Publisher: Springer Science & Business Media ISBN: 3642226612 Category : Technology & Engineering Languages : en Pages : 108
Book Description
Decision tree is a widely used form of representing algorithms and knowledge. Compact data models and fast algorithms require optimization of tree complexity. This book is a research monograph on average time complexity of decision trees. It generalizes several known results and considers a number of new problems. The book contains exact and approximate algorithms for decision tree optimization, and bounds on minimum average time complexity of decision trees. Methods of combinatorics, probability theory and complexity theory are used in the proofs as well as concepts from various branches of discrete mathematics and computer science. The considered applications include the study of average depth of decision trees for Boolean functions from closed classes, the comparison of results of the performance of greedy heuristics for average depth minimization with optimal decision trees constructed by dynamic programming algorithm, and optimization of decision trees for the corner point recognition problem from computer vision. The book can be interesting for researchers working on time complexity of algorithms and specialists in test theory, rough set theory, logical analysis of data and machine learning.
Author: Christoph Molnar Publisher: Lulu.com ISBN: 0244768528 Category : Computers Languages : en Pages : 320
Book Description
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.
Author: Sanjeev Arora Publisher: Cambridge University Press ISBN: 0521424267 Category : Computers Languages : en Pages : 609
Book Description
New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.
Author: James F. Peters Publisher: Springer ISBN: 354031850X Category : Computers Languages : en Pages : 468
Book Description
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. This third volume of the Transactions on Rough Sets presents 11 revised papers that have been through a careful peer reviewing process by the journal's Editorial Board. The research monograph "Time Complexity of Decision Trees" by Mikhail Ju. Moshkov is presented in the section on dissertation and monographs. Among the regular papers the one by Zdzislaw Pawlak entitled "Flow Graphs and Data Mining" deserves a special mention.
Author: Yee Ling Boo Publisher: Springer ISBN: 9811302928 Category : Computers Languages : en Pages : 281
Book Description
This book constitutes the refereed proceedings of the 15th Australasian Conference on Data Mining, AusDM 2017, held in Melbourne, VIC, Australia, in August 2017. The 17 revised full papers presented together with 11 research track papers and 6 application track papers were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on clustering and classification; big data; time series; outlier detection and applications; social media and applications.
Author: James F. Peters Publisher: Springer Nature ISBN: 3662627981 Category : Computers Languages : en Pages : 335
Book Description
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume XXII in the series is a continuation of a number of research streams that have grown out of the seminal work of Zdzislaw Pawlak during the first decade of the 21st century.
Author: Z. Hou Publisher: IOS Press ISBN: 1643684876 Category : Computers Languages : en Pages : 1248
Book Description
Artificial Intelligence (AI) is a rapidly developing field of computer science which integrates multiple disciplines such as computer science, psychology, and philosophy. It is a technology that develops theories, methods, technologies, and application systems to simulate, extend, and expand human intelligence by attempting to understand its essence, producing a new, intelligent machine that can respond in a way similar to human intelligence. Artificial intelligence now plays an increasingly important role in the development of global industries and economies, and as such is currently changing our world significantly, making AI research a hot topic worldwide. This book presents the proceedings of ICICTA 2023, the 16th International Conference on Intelligent Computing Technology and Automation, held on 24-25 October 2023 in Xi’an, China. The conference is an annual forum dedicated to emerging and challenging topics in AI and its applications, and its aim is to bring together an international community of researchers and practitioners in the field of AI to share the latest research achievements, discuss recent advances influence future direction, and promote the diffusion of the discipline throughout the scientific community at large. A total of 322 submissions were received for ICICTA 2023, and each paper received at least 2 review reports in a rigorous peer-review procedure. Based on these reports, 141 papers were ultimately accepted and are included in this book. The book offers a current overview of developments in AI technology, and will be of interest to all those working in the field.
Author: Igor Chikalov
Author: Igor Chikalov
Author: Christoph Molnar
Author: Sanjeev Arora
Author: James F. Peters
Author: Yee Ling Boo
Author: James F. Peters
Author: Richard E. Neapolitan
Author: Polskie Towarzystwo Matematyczne
Author: Tomasz Janowski
Author: Z. Hou