Pattern Mining With Evolutionary Algorithms PDF Download
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| Author | : Alex A. Freitas |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 272 |
| Release | : 2013-11-11 |
| Genre | : Computers |
| ISBN | : 3662049236 |
Download Data Mining and Knowledge Discovery with Evolutionary Algorithms Book in PDF, ePub and Kindle
This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics
| Author | : Sebastián Ventura |
| Publisher | : Springer |
| Total Pages | : 190 |
| Release | : 2016-06-13 |
| Genre | : Computers |
| ISBN | : 3319338587 |
Download Pattern Mining with Evolutionary Algorithms Book in PDF, ePub and Kindle
This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions. This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns. A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.
| Author | : Gisele L. Pappa |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 198 |
| Release | : 2009-10-27 |
| Genre | : Computers |
| ISBN | : 3642025412 |
Download Automating the Design of Data Mining Algorithms Book in PDF, ePub and Kindle
Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from data. We focus on genetic programming in this book because it is the paradigmatic type of machine learning method for automating the generation of programs and because it has the advantage of performing a global search in the space of candidate solutions (data mining algorithms in our case), but in principle other types of search methods for this task could be investigated in the future.
| Author | : Earl Cox |
| Publisher | : Academic Press |
| Total Pages | : 554 |
| Release | : 2005-02 |
| Genre | : Computers |
| ISBN | : 0121942759 |
Download Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration Book in PDF, ePub and Kindle
Foundations and ideas -- Principal model types -- Approaches to model building -- Fundamental concepts of fuzzy logic -- Fundamental concepts of fuzzy systems -- Fuzzy SQL and intelligent queries -- Fuzzy clustering -- Fuzzy rule induction -- Fundamental concepts of genetic algorithms -- Genetic resource scheduling optimization -- Genetic tuning of fuzzy models.
| Author | : Ashish Ghosh |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 1001 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 3642189652 |
Download Advances in Evolutionary Computing Book in PDF, ePub and Kindle
This book provides a collection of fourty articles containing new material on both theoretical aspects of Evolutionary Computing (EC), and demonstrating the usefulness/success of it for various kinds of large-scale real world problems. Around 23 articles deal with various theoretical aspects of EC and 17 articles demonstrate the success of EC methodologies. These articles are written by leading experts of the field from different countries all over the world.
| Author | : Vera Kurkova |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 518 |
| Release | : 2013-11-11 |
| Genre | : Computers |
| ISBN | : 3709162300 |
Download Artificial Neural Nets and Genetic Algorithms Book in PDF, ePub and Kindle
The first ICANNGA conference, devoted to biologically inspired computational paradigms, Neural Net works and Genetic Algorithms, was held in Innsbruck, Austria, in 1993. The meeting attracted researchers from all over Europe and further afield, who decided that this particular blend of topics should form a theme for a series of biennial conferences. The second meeting, held in Ales, France, in 1995, carried on the tradition set in Innsbruck of a relaxed and stimulating environment for the. exchange of ideas. The series has continued in Norwich, UK, in 1997, and Portoroz, Slovenia, in 1999. The Institute of Computer Science, Czech Academy of Sciences, is pleased to host the fifth conference in Prague. We have chosen the Liechtenstein palace under the Prague Castle as the conference site to enhance the traditionally good atmosphere of the meeting. There is an inspirational genius loci of the historical center of the city, where four hundred years ago a fruitful combination of theoretical and empirical method, through the collaboration of Johannes Kepler and Tycho de Brahe, led to the discovery of the laws of planetary orbits.
| Author | : Elena Marchiori |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 311 |
| Release | : 2007-04-02 |
| Genre | : Computers |
| ISBN | : 354071782X |
Download Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics Book in PDF, ePub and Kindle
This book constitutes the refereed proceedings of the 5th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2007, held in Valencia, Spain, April 2007. Coverage brings together experts in computer science with experts in bioinformatics and the biological sciences. It presents contributions on fundamental and theoretical issues along with papers dealing with different applications areas.
| Author | : Raymond Chiong |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 470 |
| Release | : 2011-11-13 |
| Genre | : Technology & Engineering |
| ISBN | : 3642234240 |
Download Variants of Evolutionary Algorithms for Real-World Applications Book in PDF, ePub and Kindle
Evolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book “Variants of Evolutionary Algorithms for Real-World Applications” aims to promote the practitioner’s view on EAs by providing a comprehensive discussion of how EAs can be adapted to the requirements of various applications in the real-world domains. It comprises 14 chapters, including an introductory chapter re-visiting the fundamental question of what an EA is and other chapters addressing a range of real-world problems such as production process planning, inventory system and supply chain network optimisation, task-based jobs assignment, planning for CNC-based work piece construction, mechanical/ship design tasks that involve runtime-intense simulations, data mining for the prediction of soil properties, automated tissue classification for MRI images, and database query optimisation, among others. These chapters demonstrate how different types of problems can be successfully solved using variants of EAs and how the solution approaches are constructed, in a way that can be understood and reproduced with little prior knowledge on optimisation.
| Author | : Sathiyamoorthi Velayutham |
| Publisher | : IGI Global, Engineering Science Reference |
| Total Pages | : 0 |
| Release | : 2019-08-23 |
| Genre | : Computers |
| ISBN | : 9781522599050 |
Download Handbook of Research on Applications and Implementations of Machine Learning Techniques Book in PDF, ePub and Kindle
"This book examines the practical applications and implementation of various machine learning techniques in various fields such as agriculture, medical, image processing, and networking"--
| Author | : R. Uday Kiran |
| Publisher | : Springer Nature |
| Total Pages | : 263 |
| Release | : 2021-10-29 |
| Genre | : Computers |
| ISBN | : 9811639647 |
Download Periodic Pattern Mining Book in PDF, ePub and Kindle
This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software. Periodic pattern mining is a popular and emerging research area in the field of data mining. It involves discovering all regularly occurring patterns in temporal databases. One of the major applications of periodic pattern mining is the analysis of customer transaction databases to discover sets of items that have been regularly purchased by customers. Discovering such patterns has several implications for understanding the behavior of customers. Since the first work on periodic pattern mining, numerous studies have been published and great advances have been made in this field. The book consists of three main parts: introduction, algorithms, and applications. The first chapter is an introduction to pattern mining and periodic pattern mining. The concepts of periodicity, periodic support, search space exploration techniques, and pruning strategies are discussed. The main types of algorithms are also presented such as periodic-frequent pattern growth, partial periodic pattern-growth, and periodic high-utility itemset mining algorithm. Challenges and research opportunities are reviewed. The chapters that follow present state-of-the-art techniques for discovering periodic patterns in (1) transactional databases, (2) temporal databases, (3) quantitative temporal databases, and (4) big data. Then, the theory on concise representations of periodic patterns is presented, as well as hiding sensitive information using privacy-preserving data mining techniques. The book concludes with several applications of periodic pattern mining, including applications in air pollution data analytics, accident data analytics, and traffic congestion analytics.
