Interpretable Artificial Intelligence: A Perspective of Granular Computing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Interpretable Artificial Intelligence: A Perspective of Granular Computing write by Witold Pedrycz. This book was released on 2021-03-26. Interpretable Artificial Intelligence: A Perspective of Granular Computing available in PDF, EPUB and Kindle. This book offers a comprehensive treatise on the recent pursuits of Artificial Intelligence (AI) – Explainable Artificial Intelligence (XAI) by casting the crucial features of interpretability and explainability in the original framework of Granular Computing. The innovative perspective established with the aid of information granules provides a high level of human centricity and transparency central to the development of AI constructs. The chapters reflect the breadth of the area and cover recent developments in the methodology, advanced algorithms and applications of XAI to visual analytics, knowledge representation, learning and interpretation. The book appeals to a broad audience including researchers and practitioners interested in gaining exposure to the rapidly growing body of knowledge in AI and intelligent systems.
Granular Computing and Intelligent Systems
Granular Computing and Intelligent Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Granular Computing and Intelligent Systems write by Witold Pedrycz. This book was released on 2011-04-28. Granular Computing and Intelligent Systems available in PDF, EPUB and Kindle. Information granules are fundamental conceptual entities facilitating perception of complex phenomena and contributing to the enhancement of human centricity in intelligent systems. The formal frameworks of information granules and information granulation comprise fuzzy sets, interval analysis, probability, rough sets, and shadowed sets, to name only a few representatives. Among current developments of Granular Computing, interesting options concern information granules of higher order and of higher type. The higher order information granularity is concerned with an effective formation of information granules over the space being originally constructed by information granules of lower order. This construct is directly associated with the concept of hierarchy of systems composed of successive processing layers characterized by the increasing levels of abstraction. This idea of layered, hierarchical realization of models of complex systems has gained a significant level of visibility in fuzzy modeling with the well-established concept of hierarchical fuzzy models where one strives to achieve a sound tradeoff between accuracy and a level of detail captured by the model and its level of interpretability. Higher type information granules emerge when the information granules themselves cannot be fully characterized in a purely numerical fashion but instead it becomes convenient to exploit their realization in the form of other types of information granules such as type-2 fuzzy sets, interval-valued fuzzy sets, or probabilistic fuzzy sets. Higher order and higher type of information granules constitute the focus of the studies on Granular Computing presented in this study. The book elaborates on sound methodologies of Granular Computing, algorithmic pursuits and an array of diverse applications and case studies in environmental studies, option price forecasting, and power engineering.
Explainable, Interpretable, and Transparent AI Systems
Explainable, Interpretable, and Transparent AI Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Explainable, Interpretable, and Transparent AI Systems write by B. K. Tripathy. This book was released on 2024-08-23. Explainable, Interpretable, and Transparent AI Systems available in PDF, EPUB and Kindle. Transparent Artificial Intelligence (AI) systems facilitate understanding of the decision-making process and provide opportunities in various aspects of explaining AI models. This book provides up-to-date information on the latest advancements in the field of explainable AI, which is a critical requirement of AI, Machine Learning (ML), and Deep Learning (DL) models. It provides examples, case studies, latest techniques, and applications from domains such as healthcare, finance, and network security. It also covers open-source interpretable tool kits so that practitioners can use them in their domains. Features: Presents a clear focus on the application of explainable AI systems while tackling important issues of “interpretability” and “transparency”. Reviews adept handling with respect to existing software and evaluation issues of interpretability. Provides insights into simple interpretable models such as decision trees, decision rules, and linear regression. Focuses on interpreting black box models like feature importance and accumulated local effects. Discusses capabilities of explainability and interpretability. This book is aimed at graduate students and professionals in computer engineering and networking communications.
Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery
Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery write by Boris Kovalerchuk. This book was released on 2024. Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery available in PDF, EPUB and Kindle. Zusammenfassung: This book continues a series of Springer publications devoted to the emerging field of Integrated Artificial Intelligence and Machine Learning with Visual Knowledge Discovery and Visual Analytics that combine advances in both fields. Artificial Intelligence and Machine Learning face long-standing challenges of explainability and interpretability that underpin trust. Such attributes are fundamental to both decision-making and knowledge discovery. Models are approximations and, at best, interpretations of reality that are transposed to algorithmic form. A visual explanation paradigm is critically important to address such challenges, as current studies demonstrate in salience analysis in deep learning for images and texts. Visualization means are generally effective for discovering and explaining high-dimensional patterns in all high-dimensional data, while preserving data properties and relations in visualizations is challenging. Recent developments, such as in General Line Coordinates, open new opportunities to address such challenges. This book contains extended papers presented in 2021 and 2022 at the International Conference on Information Visualization (IV) on AI and Visual Analytics, with 18 chapters from international collaborators. The book builds on the previous volume, published in 2022 in the Studies in Computational Intelligence. The current book focuses on the following themes: knowledge discovery with lossless visualizations, AI/ML through visual knowledge discovery with visual analytics case studies application, and visual knowledge discovery in text mining and natural language processing. The intended audience for this collection includes but is not limited to developers of emerging AI/machine learning and visualization applications, scientists, practitioners, and research students. It has multiple examples of the current integration of AI/machine learning and visualization for visual knowledge discovery, visual analytics, and text and natural language processing. The book provides case examples for future directions in this domain. New researchers find inspiration to join the profession of the field of AI/machine learning through a visualization lens.
Applied Decision-Making
Applied Decision-Making - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applied Decision-Making write by Mauricio A. Sanchez. This book was released on 2019-05-18. Applied Decision-Making available in PDF, EPUB and Kindle. This book gathers a collection of the latest research, applications, and proposals, introducing readers to innovations and concepts from diverse environments and systems. As such, it will provide students and professionals alike with not only cutting-edge information, but also new inspirations and potential research directions. Each chapter focuses on a specific aspect of applied decision making, e.g. in complex systems, computational intelligence, security, and ubiquitous computing.
