Introducing the IBM SPSS Modeler, this book guides readers through data mining processes and presents relevant statistical methods. There is a special focus on step-by-step tutorials and well-documented examples that help demystify complex mathematical algorithms and computer programs. The variety of exercises and solutions as well as an accompanying website with data sets and SPSS Modeler streams are particularly valuable. While intended for students, the simplicity of the Modeler makes the book useful for anyone wishing to learn about basic and more advanced data mining, and put this knowledge into practice.
Datenmodelle für Kernfunktionen, die in nahezu allen Geschäftsbereichen eine Rolle spielen: Dieses zweibändige, überarbeitete Handbuch in der 2. Auflage zeigt Datenbankprogrammierern, wie sie zwei Drittel der üblichen Entwicklungszeit sparen können! Neu in diesem 1. Band ist ein Kapitel zu Data Marts für die Finanzanalyse; über 30% des Stoffes wurde außerdem sorgfältig aktualisiert. Aufgenommen wurden hochaktuelle Datenmodelle, mit denen die Autoren seit dem Erscheinen der Erstauflage Erfahrungen sammeln konnten. Eine separat erhältliche CD-ROM beinhaltet sämtliche Datenmodelle in einer Form, die leicht in gebräuchliche kommerzielle Datenbanken zu integrieren ist.
A guide to task automation, custom add-on development, and procedural content generation in Blender, the free and open-source 3D graphics and animation tool. Blender Scripting with Python will teach you how to develop custom scripts and helpful add-ons to streamline and automate your workflow, as well as tricks on how to procedurally generate game level and character geometry. Once you´ve reviewed the Blender API and learned how to load and run scripts in Blender, you´ll learn how to automate tasks related to virtual reality, mesh modeling, sculpting, retopology, UV mapping, texture painting, rigging, animation, rendering, map baking, lighting, and more. You´ll also learn to create impressive demos of your add-ons and automation projects and how to package them for distribution. Packed with hands-on examples, code samples, and tips for future experimentation, Blender Scripting with Python is an all-in-one reference guide for the Blender user interested in taking control of Blender.
This book proposes a customized solution for avoiding repetitive tasks in software implementation. Reducing the time spent on these tasks is the primary objective of this project which ultimately leads to a software prototyping application. Since the modern approach of software implementation is model-driven, the proposed system will also consist the model-driven approach with its solution. This book is suitable for both undergraduate and postgraduate students.
Limited to a strict interpretation of its definition, open source consists of a set of rules which apply to a piece of software and which specify how the software and derivatives of it may be used. However, it is widely seen as much more than a simple licensing agreement, it is a ´´philoshophy´´, a ´´production model´´, a ´´way of organizing projects´´, or even ´´a new innovation model´´. But how are open source projects organized and how is work coordinated and distributed between its developers? This work contributes by examining actual source code changes, comparing 29 projects. Which developers collaborate in the same files and wich work exclusively in their own domain? Looking for patterns across projects, this work attempts to identify coordination styles in open source projects.
Modern statistics deals with large and complex data sets, and consequently with models containing a large number of parameters. This book presents a detailed account of recently developed approaches, including the Lasso and versions of it for various models, boosting methods, undirected graphical modeling, and procedures controlling false positive selections. A special characteristic of the book is that it contains comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This in-depth approach highlights the methods´ great potential and practical applicability in a variety of settings. As such, it is a valuable resource for researchers, graduate students and experts in statistics, applied mathematics and computer science.
Data alone are worth almost nothing. While data collection is increasing exponentially worldwide, a clear distinction between retrieving data and obtaining knowledge has to be made. Data are retrieved while measuring phenomena or gathering facts. Knowledge refers to data patterns and trends that are useful for decision making. Data interpretation creates a challenge that is particularly present in system identification, where thousands of models may explain a given set of measurements. Manually interpreting such data is not reliable. One solution is to use data mining. This book thus proposes an integration of techniques from data mining, a field of research where the aim is to find knowledge from data, into an existing multiple-model system identification methodology. In addition to providing information about the candidate model space, data mining is found to be a valuable tool for supporting decisions related to subsequent sensor placement.
The revised edition of this book offers an extended overview of quantum walks and explains their role in building quantum algorithms, in particular search algorithms. Updated throughout, the book focuses on core topics including Grover´s algorithm and the most important quantum walk models, such as the coined, continuous-time, and Szedgedy´s quantum walk models. There is a new chapter describing the staggered quantum walk model. The chapter on spatial search algorithms has been rewritten to offer a more comprehensive approach and a new chapter describing the element distinctness algorithm has been added. There is a new appendix on graph theory highlighting the importance of graph theory to quantum walks. As before, the reader will benefit from the pedagogical elements of the book, which include exercises and references to deepen the reader´s understanding, and guidelines for the use of computer programs to simulate the evolution of quantum walks. Review of the first edition: ´´The book is nicely written, the concepts are introduced naturally, and many meaningful connections between them are highlighted. The author proposes a series of exercises that help the reader get some working experience with the presented concepts, facilitating a better understanding. Each chapter ends with a discussion of further references, pointing the reader to major results on the topics presented in the respective chapter.´´ - Florin Manea, zbMATH.
This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organisms, and they then discuss algorithms based on formal models of foraging, how to evolve a foraging strategy, and likely future developments. No prior knowledge of natural computing is assumed. This book will be of particular interest to graduate students, academics and practitioners in computer science, informatics, data science, management science, and other application domains.
This book introduces a computationally feasible, cognitively inspired formal model of concept invention, drawing on Fauconnier and Turner´s theory of conceptual blending, a fundamental cognitive operation. The chapters present the mathematical and computational foundations of concept invention, discuss cognitive and social aspects, and further describe concrete implementations and applications in the fields of musical and mathematical creativity. Featuring contributions from leading researchers in formal systems, cognitive science, artificial intelligence, computational creativity, mathematical reasoning and cognitive musicology, the book will appeal to readers interested in how conceptual blending can be precisely characterized and implemented for the development of creative computational systems.