An efficient classification framework for breast cancer using hyper parameter tuned Random Decision Forest Classifier and Bayesian Optimization PDF Download

Author: Pratheep Kumar
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 11

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Book Description
Decision tree algorithm is one of the algorithm which is easily understandable and interpretable algorithm used in both training and application purpose during breast cancer prognosis. To address this problem, Random Decision Forests are proposed. In this manuscript, the breast cancer classification can be determined by combining the advantages of Feature Weight and Hyper Parameter Tuned Random Decision Forest classifier

Author: Janusz Kacprzyk
Publisher: Springer Nature
ISBN: 3031352483
Category : Technology & Engineering
Languages : en
Pages : 882

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Book Description
This book describes the potential contributions of emerging technologies in different fields as well as the opportunities and challenges related to the integration of these technologies in the socio-economic sector. In this book, many latest technologies are addressed, particularly in the fields of computer science and engineering. The expected scientific papers covered state-of-the-art technologies, theoretical concepts, standards, product implementation, ongoing research projects, and innovative applications of Sustainable Development. This new technology highlights, the guiding principle of innovation for harnessing frontier technologies and taking full profit from the current technological revolution to reduce gaps that hold back truly inclusive and sustainable development. The fundamental and specific topics are Big Data Analytics, Wireless sensors, IoT, Geospatial technology, Engineering and Mechanization, Modeling Tools, Risk analytics, and preventive systems.

Author: Víctor Yepes
Publisher: MDPI
ISBN: 3039436074
Category : Technology & Engineering
Languages : en
Pages : 300

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Book Description
In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner.

Author: Jason C. Hung
Publisher: Springer Nature
ISBN: 9819920922
Category : Computers
Languages : en
Pages : 1042

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Book Description
This book comprises select peer-reviewed proceedings of the 6th International Conference on Innovative Computing (IC 2023). The contents focus on communication networks, business intelligence and knowledge management, web intelligence, and fields related to the development of information technology. The chapters include contributions on various topics such as databases and data mining, networking and communications, web and Internet of Things, embedded systems, soft computing, social network analysis, security and privacy, optical communication, and ubiquitous/pervasive computing. This volume will serve as a comprehensive overview of the latest advances in information technology for those working as researchers in both academia and industry.

Author: Dilip Kumar Sarkar
Publisher: Springer Nature
ISBN: 9819927102
Category : Technology & Engineering
Languages : en
Pages : 698

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Book Description
The book is a collection of best selected research papers presented at the Fourth International Conference on Communication, Devices and Computing (ICCDC 2023). The book covers new ideas, applications and experiences of research engineers, scientists, industrialists, scholars and students from in and around the globe. It covers research contributions from communication technologies which are from the areas such as 5G communication, next-generation Wi-Fi, spread spectrum systems, satellite and high altitude platforms, radio over fiber techniques, wireless sensor networks, modulation and diversity technique, ad hoc and mesh networks, cognitive radio networking, optical wireless and visible light communications, signal processing for secure communication, millimeter wave and terahertz communication, design, control and management of optical network, error control coding and information theory, printed antennas, performance analysis of wireless network, smart antennas and space time processing.

Author: Aboul-Ella Hassanien
Publisher: Springer Nature
ISBN: 3030442896
Category : Technology & Engineering
Languages : en
Pages : 880

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Book Description
This book presents the proceedings of the 1st International Conference on Artificial Intelligence and Computer Visions (AICV 2020), which took place in Cairo, Egypt, from April 8 to 10, 2020. This international conference, which highlighted essential research and developments in the fields of artificial intelligence and computer visions, was organized by the Scientific Research Group in Egypt (SRGE). The book is divided into sections, covering the following topics: swarm-based optimization mining and data analysis, deep learning and applications, machine learning and applications, image processing and computer vision, intelligent systems and applications, and intelligent networks.

Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 012816087X
Category : Science
Languages : en
Pages : 348

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Book Description
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. - Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging - Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining - Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains

Author: Aravindan Chandrabose
Publisher: Springer Nature
ISBN: 3030634671
Category : Computers
Languages : en
Pages : 338

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Book Description
This book constitutes the refereed post-conference proceedings of the Third IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2020, held in Chennai, India, in February 2020. The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: computational intelligence for text analysis; computational intelligence for image and video analysis; and data science.

Author: Amit Kumar
Publisher: Springer Nature
ISBN: 9819780438
Category :
Languages : en
Pages : 1425

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Book Description

Author: Ying Bi
Publisher: Springer Nature
ISBN: 3030659275
Category : Technology & Engineering
Languages : en
Pages : 279

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Book Description
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.