A Genetic Programming Approach To Classification Problems
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A Genetic Programming Approach To Classification Problems
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Author : Hakan Uysal
language : en
Publisher: GRIN Verlag
Release Date : 2016-07-26
A Genetic Programming Approach To Classification Problems written by Hakan Uysal and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-26 with Computers categories.
Essay from the year 2013 in the subject Computer Science - Programming, grade: A+, University College Dublin, course: Natural Computing, language: English, abstract: Genetic Programming is a biological evolution inspired technique for computer programs to solve problems automatically by evolving iteratively using a fitness function. The advantage of this type programming is that it only defines the basics. As a result of this, it is a flexible solution for broad range of domains. Classification has been one of the most compelling problems in machine learning. In this paper, there is a comparison between genetic programming classifier and conventional classification algorithms like Naive Bayes, C4.5 decision tree, Random Forest, Support Vector Machines and k-Nearest Neighbour. The experiment is done on several data sets with different sizes, feature sets and attribute properties. There is also an experiment on the time complexity of each classifier method.
Genetic Programming For Image Classification
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Author : Ying Bi
language : en
Publisher: Springer Nature
Release Date : 2021-02-08
Genetic Programming For Image Classification written by Ying Bi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-08 with Technology & Engineering categories.
This book offers several new GP approaches to feature learning for image classification. Image classification is an important task in computer vision and machine learning with a wide range of applications. Feature learning is a fundamental step in image classification, but it is difficult due to the high variations of images. Genetic Programming (GP) is an evolutionary computation technique that can automatically evolve computer programs to solve any given problem. This is an important research field of GP and image classification. No book has been published in this field. This book shows how different techniques, e.g., image operators, ensembles, and surrogate, are proposed and employed to improve the accuracy and/or computational efficiency of GP for image classification. The proposed methods are applied to many different image classification tasks, and the effectiveness and interpretability of the learned models will be demonstrated. This book is suitable as a graduate and postgraduate level textbook in artificial intelligence, machine learning, computer vision, and evolutionary computation.
Genetic Programming Theory And Practice Xiv
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Author : Rick Riolo
language : en
Publisher: Springer
Release Date : 2018-10-24
Genetic Programming Theory And Practice Xiv written by Rick Riolo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-24 with Computers categories.
These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Chapters in this volume include: Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression Hybrid Structural and Behavioral Diversity Methods in GP Multi-Population Competitive Coevolution for Anticipation of Tax Evasion Evolving Artificial General Intelligence for Video Game Controllers A Detailed Analysis of a PushGP Run Linear Genomes for Structured Programs Neutrality, Robustness, and Evolvability in GP Local Search in GP PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification Relational Structure in Program Synthesis Problems with Analogical Reasoning An Evolutionary Algorithm for Big Data Multi-Class Classification Problems A Generic Framework for Building Dispersion Operators in the Semantic Space Assisting Asset Model Development with Evolutionary Augmentation Building Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Genetic Algorithms And Genetic Programming
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Author : Michael Affenzeller
language : en
Publisher: CRC Press
Release Date : 2009-04-09
Genetic Algorithms And Genetic Programming written by Michael Affenzeller and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-09 with Computers categories.
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for al
Genetic Programming Theory And Practice Xvi
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Author : Wolfgang Banzhaf
language : en
Publisher: Springer
Release Date : 2019-01-23
Genetic Programming Theory And Practice Xvi written by Wolfgang Banzhaf and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-23 with Computers categories.
These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: evolving developmental programs for neural networks solving multiple problems, tangled program, transfer learning and outlier detection using GP, program search for machine learning pipelines in reinforcement learning, automatic programming with GP, new variants of GP, like SignalGP, variants of lexicase selection, and symbolic regression and classification techniques. The volume includes several chapters on best practices and lessons learned from hands-on experience. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
Automating The Design Of Data Mining Algorithms
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Author : Gisele L. Pappa
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-10-27
Automating The Design Of Data Mining Algorithms written by Gisele L. Pappa 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 2009-10-27 with Computers categories.
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.
Algorithms For Regression And Classification
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Author : Robin Nunkesser
language : en
Publisher: BoD – Books on Demand
Release Date : 2009
Algorithms For Regression And Classification written by Robin Nunkesser and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
The focus of this dissertation is on robust regression and classification in genetic association studies. In the context of robust regression, new exact algorithms, results for robust online scale estimation, and an evolutionary computation algorithm for different estimators in higher dimensions are presented. For classification in genetic association studies, this thesis describes a Genetic Programming algorithm that outpeforms the standard approaches on the considered data sets.
Research Anthology On Multi Industry Uses Of Genetic Programming And Algorithms
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2020-12-05
Research Anthology On Multi Industry Uses Of Genetic Programming And Algorithms written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-05 with Computers categories.
Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.
Data Mining A Heuristic Approach
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Author : Abbass, Hussein A.
language : en
Publisher: IGI Global
Release Date : 2001-07-01
Data Mining A Heuristic Approach written by Abbass, Hussein A. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-07-01 with Computers categories.
Real life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solving methods are no longer capable of handling this level of complexity, heuristic search methods have attracted increasing attention in recent years for solving such problems. Inspired by nature, biology, statistical mechanics, physics and neuroscience, heuristics techniques are used to solve many problems where traditional methods have failed. Data Mining: A Heuristic Approach will be a repository for the applications of these techniques in the area of data mining.
Genetic Programming Theory And Practice Vii
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Author : Rick Riolo
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-11-07
Genetic Programming Theory And Practice Vii written by Rick Riolo 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 2009-11-07 with Computers categories.
Genetic Programming Theory and Practice VII presents the results of the annual Genetic Programming Theory and Practice Workshop, contributed by the foremost international researchers and practitioners in the GP arena. Contributions examine the similarities and differences between theoretical and empirical results on real-world problems, and explore the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application. Application areas include chemical process control, circuit design, financial data mining and bio-informatics, to name a few. About this book: Discusses the hurdles encountered when solving large-scale, cutting-edge applications, provides in-depth presentations of the latest and most significant applications of GP and the most recent theoretical results with direct applicability to state-of-the-art problems. Genetic Programming Theory and Practice VII is suitable for researchers, practitioners and students of Genetic Programming, including industry technical staffs, technical consultants and business entrepreneurs.