Decision Tree And Ensemble Learning Based On Ant Colony Optimization
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Decision Tree And Ensemble Learning Based On Ant Colony Optimization
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Author : Jan Kozak
language : en
Publisher: Springer
Release Date : 2018-06-20
Decision Tree And Ensemble Learning Based On Ant Colony Optimization written by Jan Kozak and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-20 with Technology & Engineering categories.
This book not only discusses the important topics in the area of machine learning and combinatorial optimization, it also combines them into one. This was decisive for choosing the material to be included in the book and determining its order of presentation. Decision trees are a popular method of classification as well as of knowledge representation. At the same time, they are easy to implement as the building blocks of an ensemble of classifiers. Admittedly, however, the task of constructing a near-optimal decision tree is a very complex process. The good results typically achieved by the ant colony optimization algorithms when dealing with combinatorial optimization problems suggest the possibility of also using that approach for effectively constructing decision trees. The underlying rationale is that both problem classes can be presented as graphs. This fact leads to option of considering a larger spectrum of solutions than those based on the heuristic. Moreover, ant colony optimization algorithms can be used to advantage when building ensembles of classifiers. This book is a combination of a research monograph and a textbook. It can be used in graduate courses, but is also of interest to researchers, both specialists in machine learning and those applying machine learning methods to cope with problems from any field of R&D.
Decision Tree And Ensemble Learning Based On Ant Colony Optimization
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Author : Jan Kozak
language : en
Publisher:
Release Date : 2019
Decision Tree And Ensemble Learning Based On Ant Colony Optimization written by Jan Kozak and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Ant algorithms categories.
This book not only discusses the important topics in the area of machine learning and combinatorial optimization, it also combines them into one. This was decisive for choosing the material to be included in the book and determining its order of presentation. Decision trees are a popular method of classification as well as of knowledge representation. At the same time, they are easy to implement as the building blocks of an ensemble of classifiers. Admittedly, however, the task of constructing a near-optimal decision tree is a very complex process. The good results typically achieved by the ant colony optimization algorithms when dealing with combinatorial optimization problems suggest the possibility of also using that approach for effectively constructing decision trees. The underlying rationale is that both problem classes can be presented as graphs. This fact leads to option of considering a larger spectrum of solutions than those based on the heuristic. Moreover, ant colony optimization algorithms can be used to advantage when building ensembles of classifiers. This book is a combination of a research monograph and a textbook. It can be used in graduate courses, but is also of interest to researchers, both specialists in machine learning and those applying machine learning methods to cope with problems from any field of R & D.
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.
Machine Learning Methods For Pain Investigation Using Physiological Signals
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Author : Philip Johannes Gouverneur
language : en
Publisher: Logos Verlag Berlin GmbH
Release Date : 2024-06-14
Machine Learning Methods For Pain Investigation Using Physiological Signals written by Philip Johannes Gouverneur and has been published by Logos Verlag Berlin GmbH this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-14 with Mathematics categories.
Pain assessment has remained largely unchanged for decades and is currently based on self-reporting. Although there are different versions, these self-reports all have significant drawbacks. For example, they are based solely on the individual’s assessment and are therefore influenced by personal experience and highly subjective, leading to uncertainty in ratings and difficulty in comparability. Thus, medicine could benefit from an automated, continuous and objective measure of pain. One solution is to use automated pain recognition in the form of machine learning. The aim is to train learning algorithms on sensory data so that they can later provide a pain rating. This thesis summarises several approaches to improve the current state of pain recognition systems based on physiological sensor data. First, a novel pain database is introduced that evaluates the use of subjective and objective pain labels in addition to wearable sensor data for the given task. Furthermore, different feature engineering and feature learning approaches are compared using a fair framework to identify the best methods. Finally, different techniques to increase the interpretability of the models are presented. The results show that classical hand-crafted features can compete with and outperform deep neural networks. Furthermore, the underlying features are easily retrieved from electrodermal activity for automated pain recognition, where pain is often associated with an increase in skin conductance.
Machine Learning Based Modelling In Atomic Layer Deposition Processes
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Author : Oluwatobi Adeleke
language : en
Publisher: CRC Press
Release Date : 2023-12-15
Machine Learning Based Modelling In Atomic Layer Deposition Processes written by Oluwatobi Adeleke and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-15 with Technology & Engineering categories.
While thin film technology has benefited greatly from artificial intelligence (AI) and machine learning (ML) techniques, there is still much to be learned from a full-scale exploration of these technologies in atomic layer deposition (ALD). This book provides in-depth information regarding the application of ML-based modeling techniques in thin film technology as a standalone approach and integrated with the classical simulation and modeling methods. It is the first of its kind to present detailed information regarding approaches in ML-based modeling, optimization, and prediction of the behaviors and characteristics of ALD for improved process quality control and discovery of new materials. As such, this book fills significant knowledge gaps in the existing resources as it provides extensive information on ML and its applications in film thin technology. Offers an in-depth overview of the fundamentals of thin film technology, state-of-the-art computational simulation approaches in ALD, ML techniques, algorithms, applications, and challenges. Establishes the need for and significance of ML applications in ALD while introducing integration approaches for ML techniques with computation simulation approaches. Explores the application of key techniques in ML, such as predictive analysis, classification techniques, feature engineering, image processing capability, and microstructural analysis of deep learning algorithms and generative model benefits in ALD. Helps readers gain a holistic understanding of the exciting applications of ML-based solutions to ALD problems and apply them to real-world issues. Aimed at materials scientists and engineers, this book fills significant knowledge gaps in existing resources as it provides extensive information on ML and its applications in film thin technology. It also opens space for future intensive research and intriguing opportunities for ML-enhanced ALD processes, which scale from academic to industrial applications.
Computational Collective Intelligence
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Author : Ngoc Thanh Nguyen
language : en
Publisher: Springer Nature
Release Date : 2021-09-29
Computational Collective Intelligence written by Ngoc Thanh Nguyen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-29 with Computers categories.
This book constitutes the refereed proceedings of the 13th International Conference on Computational Collective Intelligence, ICCCI 2021, held in September/October 2021. The conference was held virtually due to the COVID-19 pandemic. The 58 full papers were carefully reviewed and selected from 230 submissions. The papers are grouped in topical issues on knowledge engineering and semantic web; social networks and recommender systems; collective decision-making; cooperative strategies for decision making and optimization; data mining and machine learning; computer vision techniques; natural language processing; Internet of Things: technologies and applications; Internet of Things and computational technologies for collective intelligence; computational intelligence for multimedia understanding.
Modern Optimization Techniques For Smart Grids
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Author : Adel Ali Abou El-Ela
language : en
Publisher: Springer Nature
Release Date : 2022-09-15
Modern Optimization Techniques For Smart Grids written by Adel Ali Abou El-Ela and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-15 with Technology & Engineering categories.
Modern Optimization Techniques for Smart Grids presents current research and methods for monitoring transmission systems and enhancing distribution system performance using optimization techniques considering the role of different single and multi-objective functions. The authors present in-depth information on integrated systems for smart transmission and distribution, including using smart meters such as phasor measurement units (PMUs), enhancing distribution system performance using the optimal placement of distributed generations (DGs) and/or capacitor banks, and optimal capacitor placement for power loss reduction and voltage profile improvement. The book will be a valuable reference for researchers, students, and engineers working in electrical power engineering and renewable energy systems. Predicts future development of hybrid power systems; Introduces enhanced optimization strategies; Includes MATLAB M-file codes.
Aiding Forensic Investigation Through Deep Learning And Machine Learning Frameworks
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Author : Raj, Alex Noel Joseph
language : en
Publisher: IGI Global
Release Date : 2022-06-24
Aiding Forensic Investigation Through Deep Learning And Machine Learning Frameworks written by Raj, Alex Noel Joseph and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-24 with Law categories.
It is crucial that forensic science meets challenges such as identifying hidden patterns in data, validating results for accuracy, and understanding varying criminal activities in order to be authoritative so as to hold up justice and public safety. Artificial intelligence, with its potential subsets of machine learning and deep learning, has the potential to transform the domain of forensic science by handling diverse data, recognizing patterns, and analyzing, interpreting, and presenting results. Machine Learning and deep learning frameworks, with developed mathematical and computational tools, facilitate the investigators to provide reliable results. Further study on the potential uses of these technologies is required to better understand their benefits. Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks provides an outline of deep learning and machine learning frameworks and methods for use in forensic science to produce accurate and reliable results to aid investigation processes. The book also considers the challenges, developments, advancements, and emerging approaches of deep learning and machine learning. Covering key topics such as biometrics, augmented reality, and fraud investigation, this reference work is crucial for forensic scientists, law enforcement, computer scientists, researchers, scholars, academicians, practitioners, instructors, and students.
Marketing Analytics Creating Customer Centric Culture
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Author : Joseph B. Rivera
language : en
Publisher: Joseph B. Rivera
Release Date : 2020-02-17
Marketing Analytics Creating Customer Centric Culture written by Joseph B. Rivera and has been published by Joseph B. Rivera this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-17 with Business & Economics categories.
A game-changing approach to marketing by an experienced author, speaker and businessman Joseph B. Rivera. Joseph B. Rivera has first-hand experience in business. He has learned everything through hard work and perseverance, and has inspired quite a lot of entrepreneurs, businessmen, executives, employees, and business students to challenge themselves in this modern era of commerce. For the first time, Joseph B. Rivera offers his years of experience and wisdom in this one compact, very accessible and enduring masterpiece. MARKETING ANALYTICS: CREATING CUSTOMER-CENTRIC CULTURE helps you to create a transformative culture toward excellence in your business. Whether you are an executive, businessman, business owner, investor, marketer, trainer, speaker or a student of marketing, you will be proud of what you will learn. When applied right, you will change the way products and services are designed, created and offered to the world. This book teaches you how to meaningfully connect emotionally and practically to your consumers. Remember, it is not just all about the money. Here, Joseph has put together his passion, insights, observation and experience to mentor you: ✔️How to understand the needs of the market. ✔️How to position your business. ✔️How to overcome competition. ✔️How to revolutionize your business. Learn the art or marketing analytics, and be a game changer.
Availability Reliability And Security
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Author : Florian Skopik
language : en
Publisher: Springer Nature
Release Date : 2025-08-09
Availability Reliability And Security written by Florian Skopik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-09 with Computers categories.
This two-volume set LNCS 15998-15999 constitutes the proceedings of the ARES 2025 EU Projects Symposium Workshops, held under the umbrella of the 20th International conference on Availability, Reliability and Security, ARES 2025, which took place in Ghent, Belgium, during August 11-14, 2025. The 42 full papers presented in this book were carefully reviewed and selected from 92 submissions. They contain papers of the following workshops: Part I: 5th International Workshop on Advances on Privacy Preserving Technologies and Solutions (IWAPS 2025); 6th Workshop on Security, Privacy, and Identity Management in the Cloud (SECPID 2025); First International Workshop on Secure, Trustworthy, and Robust AI (STRAI 2025); 5th International Workshop on Security and Privacy in Intelligent Infrastructures (SP2I 2025). Part II: 5th workshop on Education, Training and Awareness in Cybersecurity (ETACS 2025); 5th International Workshop on Security Testing and Monitoring (STAM 2025); 8th International Workshop on Emerging Network Security (ENS 2025).