Average Time Complexity Of Decision Trees
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Average Time Complexity Of Decision Trees
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Author : Igor Chikalov
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-04
Average Time Complexity Of Decision Trees written by Igor Chikalov and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-04 with Computers categories.
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.
Decision Support System
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Author : Susmita Bandyopadhyay
language : en
Publisher: CRC Press
Release Date : 2023-03-13
Decision Support System written by Susmita Bandyopadhyay and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-13 with Business & Economics categories.
This book presents different tools and techniques used for Decision Support Systems (DSS), including decision tree and table, and their modifications, multi-criteria decision analysis techniques, network tools of decision support, and various case-based reasoning methods supported by examples and case studies. Latest developments for each of the techniques have been discussed separately, and possible future research areas are duly identified as intelligent and spatial DSS. Features: Discusses all the major tools and techniques for Decision Support System supported by examples. Explains techniques considering their deterministic and stochastic aspects. Covers network tools including GERT and Q-GERT. Explains the application of both probability and fuzzy orientation in the pertinent techniques. Includes a number of relevant case studies along with a dedicated chapter on software. This book is aimed at researchers and graduate students in information systems, data analytics, operation research, including management and computer science areas.
Combinatorial Machine Learning
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Author : Mikhail Moshkov
language : en
Publisher: Springer
Release Date : 2011-06-29
Combinatorial Machine Learning written by Mikhail Moshkov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-29 with Computers categories.
Decision trees and decision rule systems are widely used in different applications as algorithms for problem solving, as predictors, and as a way for knowledge representation. Reducts play key role in the problem of attribute (feature) selection. The aims of this book are (i) the consideration of the sets of decision trees, rules and reducts; (ii) study of relationships among these objects; (iii) design of algorithms for construction of trees, rules and reducts; and (iv) obtaining bounds on their complexity. Applications for supervised machine learning, discrete optimization, analysis of acyclic programs, fault diagnosis, and pattern recognition are considered also. This is a mixture of research monograph and lecture notes. It contains many unpublished results. However, proofs are carefully selected to be understandable for students. The results considered in this book can be useful for researchers in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory and logical analysis of data. The book can be used in the creation of courses for graduate students.
Computational Methods For Data Analysis
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Author : Yeliz Karaca
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2018-12-17
Computational Methods For Data Analysis written by Yeliz Karaca and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-17 with Mathematics categories.
This graduate text covers a variety of mathematical and statistical tools for the analysis of big data coming from biology, medicine and economics. Neural networks, Markov chains, tools from statistical physics and wavelet analysis are used to develop efficient computational algorithms, which are then used for the processing of real-life data using Matlab.
Machine Intelligence 15
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Author : Koichi Furukawa
language : en
Publisher: Oxford University Press
Release Date : 1999
Machine Intelligence 15 written by Koichi Furukawa and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Business & Economics categories.
Following on from previous volumes in the series, Machine Intelligence 15 provides an overview of current areas of interest in artificial intelligence.
Design And Analysis Of Algorithms
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Author : DR. B. SHADAKSHARAPPA
language : en
Publisher: Book Rivers
Release Date : 2021-11-24
Design And Analysis Of Algorithms written by DR. B. SHADAKSHARAPPA and has been published by Book Rivers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-24 with Antiques & Collectibles categories.
Extensions Of Dynamic Programming For Combinatorial Optimization And Data Mining
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Author : Hassan AbouEisha
language : en
Publisher: Springer
Release Date : 2018-05-22
Extensions Of Dynamic Programming For Combinatorial Optimization And Data Mining written by Hassan AbouEisha and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-22 with Technology & Engineering categories.
Dynamic programming is an efficient technique for solving optimization problems. It is based on breaking the initial problem down into simpler ones and solving these sub-problems, beginning with the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. This book develops extensions of dynamic programming, enabling us to (i) describe the set of objects under consideration; (ii) perform a multi-stage optimization of objects relative to different criteria; (iii) count the number of optimal objects; (iv) find the set of Pareto optimal points for bi-criteria optimization problems; and (v) to study relationships between two criteria. It considers various applications, including optimization of decision trees and decision rule systems as algorithms for problem solving, as ways for knowledge representation, and as classifiers; optimization of element partition trees for rectangular meshes, which are used in finite element methods for solving PDEs; and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths. The results presented are useful for researchers in combinatorial optimization, data mining, knowledge discovery, machine learning, and finite element methods, especially those working in rough set theory, test theory, logical analysis of data, and PDE solvers. This book can be used as the basis for graduate courses.
Computational Complexity
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Author : Sanjeev Arora
language : en
Publisher: Cambridge University Press
Release Date : 2009-04-20
Computational Complexity written by Sanjeev Arora and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-20 with Computers categories.
New and classical results in computational complexity, including interactive proofs, PCP, derandomization, and quantum computation. Ideal for graduate students.
Interpretable Machine Learning
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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020
Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.
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.
Transactions On Rough Sets Iii
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Author : James F. Peters
language : en
Publisher: Springer
Release Date : 2005-05-02
Transactions On Rough Sets Iii written by James F. Peters and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-05-02 with Computers categories.
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.