Meta Learning In Decision Tree Induction
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Meta Learning In Decision Tree Induction
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Author : Krzysztof Grąbczewski
language : en
Publisher: Springer
Release Date : 2013-09-11
Meta Learning In Decision Tree Induction written by Krzysztof Grąbczewski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-11 with Technology & Engineering categories.
The book focuses on different variants of decision tree induction but also describes the meta-learning approach in general which is applicable to other types of machine learning algorithms. The book discusses different variants of decision tree induction and represents a useful source of information to readers wishing to review some of the techniques used in decision tree learning, as well as different ensemble methods that involve decision trees. It is shown that the knowledge of different components used within decision tree learning needs to be systematized to enable the system to generate and evaluate different variants of machine learning algorithms with the aim of identifying the top-most performers or potentially the best one. A unified view of decision tree learning enables to emulate different decision tree algorithms simply by setting certain parameters. As meta-learning requires running many different processes with the aim of obtaining performance results, a detailed description of the experimental methodology and evaluation framework is provided. Meta-learning is discussed in great detail in the second half of the book. The exposition starts by presenting a comprehensive review of many meta-learning approaches explored in the past described in literature, including for instance approaches that provide a ranking of algorithms. The approach described can be related to other work that exploits planning whose aim is to construct data mining workflows. The book stimulates interchange of ideas between different, albeit related, approaches.
Meta Learning In Decision Tree Induction
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Author : Krzysztof Gr Bczewski
language : en
Publisher:
Release Date : 2013-09-30
Meta Learning In Decision Tree Induction written by Krzysztof Gr Bczewski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-30 with categories.
Automatic Design Of Decision Tree Induction Algorithms
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Author : Rodrigo C. Barros
language : en
Publisher: Springer
Release Date : 2015-02-04
Automatic Design Of Decision Tree Induction Algorithms written by Rodrigo C. Barros and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-04 with Computers categories.
Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain of interest. For such, they discuss how one can effectively discover the most suitable set of components of decision-tree induction algorithms to deal with a wide variety of applications through the paradigm of evolutionary computation, following the emergence of a novel field called hyper-heuristics. "Automatic Design of Decision-Tree Induction Algorithms" would be highly useful for machine learning and evolutionary computation students and researchers alike.
Artificial Intelligence Applications And Innovations
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Author : Ilias Maglogiannis
language : en
Publisher: Springer Nature
Release Date : 2022-06-16
Artificial Intelligence Applications And Innovations written by Ilias Maglogiannis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-16 with Computers categories.
This book constitutes the refereed proceedings of five International Workshops held as parallel events of the 18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022, virtually and in Hersonissos, Crete, Greece, in June 2022: the 11th Mining Humanistic Data Workshop (MHDW 2022); the 7th 5G-Putting Intelligence to the Network Edge Workshop (5G-PINE 2022); the 1st workshop on AI in Energy, Building and Micro-Grids (AIBMG 2022); the 1st Workshop/Special Session on Machine Learning and Big Data in Health Care (ML@HC 2022); and the 2nd Workshop on Artificial Intelligence in Biomedical Engineering and Informatics (AIBEI 2022). The 35 full papers presented at these workshops were carefully reviewed and selected from 74 submissions.
Proceedings Of The Fifth Siam International Conference On Data Mining
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Author : Hillol Kargupta
language : en
Publisher: SIAM
Release Date : 2005-04-01
Proceedings Of The Fifth Siam International Conference On Data Mining written by Hillol Kargupta and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-01 with Mathematics categories.
The Fifth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. The field of data mining draws upon extensive work in areas such as statistics, machine learning, pattern recognition, databases, and high performance computing to discover interesting and previously unknown information in data. This conference results in data mining, including applications, algorithms, software, and systems.
Artificial Intelligence For Cognitive Modeling
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Author : Pijush Dutta
language : en
Publisher: CRC Press
Release Date : 2023-04-19
Artificial Intelligence For Cognitive Modeling written by Pijush Dutta and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-19 with Computers categories.
This book is written in a clear and thorough way to cover both the traditional and modern uses of artificial intelligence and soft computing. It gives an in-depth look at mathematical models, algorithms, and real-world problems that are hard to solve in MATLAB. The book is intended to provide a broad and in-depth understanding of fuzzy logic controllers, genetic algorithms, neural networks, and hybrid techniques such as ANFIS and the GA-ANN model. Features: A detailed description of basic intelligent techniques (fuzzy logic, genetic algorithm and neural network using MATLAB) A detailed description of the hybrid intelligent technique called the adaptive fuzzy inference technique (ANFIS) Formulation of the nonlinear model like analysis of ANOVA and response surface methodology Variety of solved problems on ANOVA and RSM Case studies of above mentioned intelligent techniques on the different process control systems This book can be used as a handbook and a guide for students of all engineering disciplines, operational research areas, computer applications, and for various professionals who work in the optimization area.
Evolutionary Decision Trees In Large Scale Data Mining
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Author : Marek Kretowski
language : en
Publisher: Springer
Release Date : 2019-06-05
Evolutionary Decision Trees In Large Scale Data Mining written by Marek Kretowski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-05 with Computers categories.
This book presents a unified framework, based on specialized evolutionary algorithms, for the global induction of various types of classification and regression trees from data. The resulting univariate or oblique trees are significantly smaller than those produced by standard top-down methods, an aspect that is critical for the interpretation of mined patterns by domain analysts. The approach presented here is extremely flexible and can easily be adapted to specific data mining applications, e.g. cost-sensitive model trees for financial data or multi-test trees for gene expression data. The global induction can be efficiently applied to large-scale data without the need for extraordinary resources. With a simple GPU-based acceleration, datasets composed of millions of instances can be mined in minutes. In the event that the size of the datasets makes the fastest memory computing impossible, the Spark-based implementation on computer clusters, which offers impressive fault tolerance and scalability potential, can be applied.
Data Mining And Knowledge Discovery Handbook
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Author : Oded Maimon
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-10
Data Mining And Knowledge Discovery Handbook written by Oded Maimon 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 2010-09-10 with Computers categories.
Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data. Data Mining and Knowledge Discovery Handbook, Second Edition organizes the most current concepts, theories, standards, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This handbook first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook, Second Edition is designed for research scientists, libraries and advanced-level students in computer science and engineering as a reference. This handbook is also suitable for professionals in industry, for computing applications, information systems management, and strategic research management.
Biomedical Engineering Systems And Technologies
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Author : Ana Fred
language : en
Publisher: Springer
Release Date : 2011-03-02
Biomedical Engineering Systems And Technologies written by Ana Fred and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-02 with Computers categories.
This book constitutes the thoroughly refereed post-conference proceedings of the Third International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2010, held in Valencia, Spain, in January 2010. The 30 revised full papers presented together with 1 invited lecture were carefully reviewed and selected from a total of 410 submissions in two rounds of reviewing and improvement. The papers cover a wide range of topics and are organized in four general topical sections on healthinf, biodevices, biosignals, and bioinformatics.
Data Mining And Knowledge Discovery Handbook
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Author : Oded Z. Maimon
language : en
Publisher: Springer Science & Business Media
Release Date : 2005
Data Mining And Knowledge Discovery Handbook written by Oded Z. Maimon 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 2005 with Computers categories.
Organizes major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD). This book provides algorithmic descriptions of classic methods, and also suitable for professionals in fields such as computing applications, information systems management, and more.