This book combines the advantages of high-dimensional data visualization and machine learning in the context of identifying complex n-D data patterns. It vastly expands the class of reversible lossless 2-D and 3-D visualization methods, which preserve the n-D information. This class of visual representations, called the General Lines Coordinates (GLCs), is accompanied by a set of algorithms for n-D data classification, clustering, dimension reduction, and Pareto optimization. The mathematical and theoretical analyses and methodology of GLC are included, and the usefulness of this new approach is demonstrated in multiple case studies. These include the Challenger disaster, world hunger data, health monitoring, image processing, text classification, market forecasts for a currency exchange rate, computer-aided medical diagnostics, and others. As such, the book offers a unique resource for students, researchers, and practitioners in the emerging field of Data Science.
Described by the philosopher A.J. Ayer as a work ´of great originality and power´ Popper´s The Logic of Scientific Discovery revolutionized contemporary thinking on science and knowledge. Ideas such as his now legendary doctrine of ´falsificationism´ electrified the scientific community, influencing even working scientists. The book also had a profound effect on post war philosophy. First published in English in 1959, this astonishing work ranks alongside The Open Society and Its Enemies as one of Popper´s most enduring and famous books and contains insights and arguments that demand to be read to this day.
In this book Peter Burke adopts a socio-cultural approach to examine the changes in the organization of knowledge in Europe from the invention of printing to the publication of the French Encyclopédie.The book opens with an assessment of different sociologies of knowledge from Mannheim to Foucault and beyond, and goes on to discuss intellectuals as a social group and the social institutions (especially universities and academies) which encouraged or discouraged intellectual innovation. Then, in a series of separate chapters, Burke explores the geography, anthropology, politics and economics of knowledge, focusing on the role of cities, academies, states and markets in the process of gathering, classifying, spreading and sometimes concealing information. The final chapters deal with knowledge from the point of view of the individual reader, listener, viewer or consumer, including the problem of the reliability of knowledge discussed so vigorously in the seventeenth century.One of the most original features of this book is its discussion of knowledges in the plural. It centres on printed knowledge, especially academic knowledge, but it treats the history of the knowledge ´explosion´ which followed the invention of printing and the discovery of the world beyond Europe as a process of exchange or negotiation between different knowledges, such as male and female, theoretical and practical, high-status and low-status, and European and non-European.Although written primarily as a contribution to social or socio-cultural history, this book will also be of interest to historians of science, sociologists, anthropologists, geographers and others in another age of information explosion.
This adventure in science and imagination, which the Medical Tribune said might herald ´´a Copernican revolution for the life sciences,´´ leads the reader through unexplored jungles and uncharted aspects of mind to the heart of knowledge.In a first-person narrative of scientific discovery that opens new perspectives on biology, anthropology, and the limits of rationalism, The Cosmic Serpent reveals how startlingly different the world around us appears when we open our minds to it.
This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.
El objetivo del presente libro es introducir al lector en el proceso Metodología Knowledge Discovery in Databases - KDD, minería de datos, a las técnicas de árboles de decisión, reglas de decisión, segmentación (clústeres), ofreciendo una guía en el desarrollo de modelos descriptivos y predictivos que al final faciliten la toma de decisiones en una organización, a partir de la herramienta WEKA. VENTAJAS -La autora del libro cuenta con una amplia experiencia en la docencia en el área de la informática, así como consultor, analista de sistemas. CONOZCA -El desarrollo de modelos descriptivos y predictivos que faciliten la toma de decisiones en una organización. APRENDA -Modelos descriptivos y predictivos que faciliten la toma de decisión al interior de una organización. -Las características de la herramienta WEKA. A QUIÉN VA DIRIGIDO La publicación está dirigida a estudiantes y profesionales de las carreras de Administración, Ingeniería Industrial, Economía, Estadística y afines a los trabajos de producción y administración.
These proceedings gather outstanding research papers presented at the Second International Conference on Data Engineering 2015 (DaEng-2015) and offer a consolidated overview of the latest developments in databases, information retrieval, data mining and knowledge management. The conference brought together researchers and practitioners from academia and industry to address key challenges in these fields, discuss advanced data engineering concepts and form new collaborations. The topics covered include but are not limited to: - Data engineering - Big data - Data and knowledge visualization - Data management - Data mining and warehousing - Data privacy & security - Database theory - Heterogeneous databases - Knowledge discovery in databases - Mobile, grid and cloud computing - Knowledge management - Parallel and distributed data - Temporal data - Web data, services and information engineering - Decision support systems - E-Business engineering and management - E-commerce and e-learning - Geographical information systems - Information management - Information quality and strategy - Information retrieval, integration and visualization - Information security - Information systems and technologies
Parasiticide Discovery: In Vitro and In Vivo Tests with Relevant Parasite Rearing and Host Infection/Infestation Methods, Volume One presents valuable screening methods that have led to the discovery of the majority of parasiticides commercialized in the animal health industry. As much of the knowledge of parasiticide discovery methods is being lost in the animal health industry as seasoned parasitologists retire, this book serves to preserve valuable methods that have led to the discovery of the majority of parasiticides commercialized in animal health, also giving insights into the in vitro and in vivo methods used to identify the parasiticide activity of compounds. Addresses current issues of resistance, along with combination uses for resistant parasites Presents useful, authoritative information (chemical, pharmaceutical, clinical, etc.) for the pyrantel family of compounds Includes a discussion on screening methods in combination therapies Provides cutting-edge material for an evolving area of scientific discussion Includes in vitro and in vivo screens and parasite maintenance and culture methods
Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum. The ability to detect unseen patterns hidden in the numbers exhaustively generated by day-to-day operations allows savvy decision-makers to exploit every tool at their disposal in the pursuit of better business. By creating models and testing whether patterns hold up, it is possible to discover new intelligence that could change your business´s entire paradigm for a more successful outcome. Data Mining for Dummies shows you why it doesn´t take a data scientist to gain this advantage, and empowers average business people to start shaping a process relevant to their business´s needs. In this book, you´ll learn the hows and whys of mining to the depths of your data, and how to make the case for heavier investment into data mining capabilities. The book explains the details of the knowledge discovery process including: * Model creation, validity testing, and interpretation * Effective communication of findings * Available tools, both paid and open-source * Data selection, transformation, and evaluation Data Mining for Dummies takes you step-by-step through a real-world data-mining project using open-source tools that allow you to get immediate hands-on experience working with large amounts of data. You´ll gain the confidence you need to start making data mining practices a routine part of your successful business. If you´re serious about doing everything you can to push your company to the top, Data Mining for Dummies is your ticket to effective data mining.