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EBookClubs

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Book Decision Trees for Decision Making

Download or read book Decision Trees for Decision Making written by John F. Magee and published by . This book was released on 1964 with total page 13 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Ethnographic Decision Tree Modeling

Download or read book Ethnographic Decision Tree Modeling written by Christina H. Gladwin and published by SAGE. This book was released on 1989-09 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why do people in a certain group behave the way they do? And, more importantly, what specific criteria was used by the group in question? This book presents a method for answering these questions.

Book The Decision Model

    Book Details:
  • Author : Barbara von Halle
  • Publisher : CRC Press
  • Release : 2009-10-27
  • ISBN : 1420082825
  • Pages : 556 pages

Download or read book The Decision Model written by Barbara von Halle and published by CRC Press. This book was released on 2009-10-27 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the current fast-paced and constantly changing business environment, it is more important than ever for organizations to be agile, monitor business performance, and meet with increasingly stringent compliance requirements. Written by pioneering consultants and bestselling authors with track records of international success, The Decision Model: A

Book Decision Trees for Analytics Using SAS Enterprise Miner

Download or read book Decision Trees for Analytics Using SAS Enterprise Miner written by Barry De Ville and published by . This book was released on 2019-07-03 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision Trees for Analytics Using SAS Enterprise Miner is the most comprehensive treatment of decision tree theory, use, and applications available in one easy-to-access place. This book illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements data mining approaches such as regression, as well as other business intelligence applications that incorporate tabular reports, OLAP, or multidimensional cubes. An expanded and enhanced release of Decision Trees for Business Intelligence and Data Mining Using SAS Enterprise Miner, this book adds up-to-date treatments of boosting and high-performance forest approaches and rule induction. There is a dedicated section on the most recent findings related to bias reduction in variable selection. It provides an exhaustive treatment of the end-to-end process of decision tree construction and the respective considerations and algorithms, and it includes discussions of key issues in decision tree practice. Analysts who have an introductory understanding of data mining and who are looking for a more advanced, in-depth look at the theory and methods of a decision tree approach to business intelligence and data mining will benefit from this book.

Book Management Decision Making

Download or read book Management Decision Making written by George E. Monahan and published by Cambridge University Press. This book was released on 2000-08-17 with total page 760 pages. Available in PDF, EPUB and Kindle. Book excerpt: CD-ROM contains: Crystal Ball -- TreePlan -- AnimaLP -- Queue -- ExcelWorkbooks.

Book Spreadsheet Modeling for Business Decisions   Webcom

Download or read book Spreadsheet Modeling for Business Decisions Webcom written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Alternative Decision Making Models for Financial Portfolio Management  Emerging Research and Opportunities

Download or read book Alternative Decision Making Models for Financial Portfolio Management Emerging Research and Opportunities written by Spaseski, Narela and published by IGI Global. This book was released on 2017-08-11 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economics is an integral aspect to every successful society, yet basic financial practices have gone unchanged for decades. Analyzing unconventional finance methods can provide new ways to ensure personal financial futures on an individual level, as well as boosting international economies. Alternative Decision-Making Models for Financial Portfolio Management: Emerging Research and Opportunities is an essential reference source that discusses methods and techniques that make financial administration more efficient for professionals in economic fields. Featuring relevant topics such as mean-variance portfolio theory, decision tree analysis, risk protection strategies, and asset-liability management, this publication is ideal for academicians, students, economists, and researchers that would like to stay current on new and innovative methods to transform the financial realm.

Book Data Mining With Decision Trees  Theory And Applications  2nd Edition

Download or read book Data Mining With Decision Trees Theory And Applications 2nd Edition written by Oded Z Maimon and published by World Scientific. This book was released on 2014-09-03 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced.This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition.This book invites readers to explore the many benefits in data mining that decision trees offer:

Book Decision Trees for Business Intelligence and Data Mining

Download or read book Decision Trees for Business Intelligence and Data Mining written by Barry De Ville and published by SAS Press. This book was released on 2006 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements other business intelligence applications.

Book Probability Models for Economic Decisions  second edition

Download or read book Probability Models for Economic Decisions second edition written by Roger B. Myerson and published by MIT Press. This book was released on 2019-12-17 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the use of probability models for analyzing risk and economic decisions, using spreadsheets to represent and simulate uncertainty. This textbook offers an introduction to the use of probability models for analyzing risks and economic decisions. It takes a learn-by-doing approach, teaching the student to use spreadsheets to represent and simulate uncertainty and to analyze the effect of such uncertainty on an economic decision. Students in applied business and economics can more easily grasp difficult analytical methods with Excel spreadsheets. The book covers the basic ideas of probability, how to simulate random variables, and how to compute conditional probabilities via Monte Carlo simulation. The first four chapters use a large collection of probability distributions to simulate a range of problems involving worker efficiency, market entry, oil exploration, repeated investment, and subjective belief elicitation. The book then covers correlation and multivariate normal random variables; conditional expectation; optimization of decision variables, with discussions of the strategic value of information, decision trees, game theory, and adverse selection; risk sharing and finance; dynamic models of growth; dynamic models of arrivals; and model risk. New material in this second edition includes two new chapters on additional dynamic models and model risk; new sections in every chapter; many new end-of-chapter exercises; and coverage of such topics as simulation model workflow, models of probabilistic electoral forecasting, and real options. The book comes equipped with Simtools, an open-source, free software used througout the book, which allows students to conduct Monte Carlo simulations seamlessly in Excel.

Book Applying Predictive Analytics

Download or read book Applying Predictive Analytics written by Richard V. McCarthy and published by Springer. This book was released on 2019-03-12 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life example of how business analytics have been used in various aspects of organizations to solve issue or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes.

Book Business analyst  a profession and a mindset

Download or read book Business analyst a profession and a mindset written by Yulia Kosarenko and published by Yulia Kosarenko. This book was released on 2019-05-12 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: What does it mean to be a business analyst? What would you do every day? How will you bring value to your clients? And most importantly, what makes a business analyst exceptional? This book will answer your questions about this challenging career choice through the prism of the business analyst mindset — a concept developed by the author, and its twelve principles demonstrated through many case study examples. "Business analyst: a profession and a mindset" is a structurally rich read with over 90 figures, tables and models. It offers you more than just techniques and methodologies. It encourages you to understand people and their behaviour as the key to solving business problems.

Book Data Mining and Knowledge Discovery Handbook

Download or read book Data Mining and Knowledge Discovery Handbook written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2006-05-28 with total page 1378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.

Book The Three Pillar Model for Business Decisions  Strategy  Law and Ethics

Download or read book The Three Pillar Model for Business Decisions Strategy Law and Ethics written by George J. Siedel and published by Van Rye Publishing, LLC. This book was released on 2016-03-21 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will show you how to use an expanded version of the decision-making model taught in the leadership course for Harvard MBA students. Based on a Strategy Pillar, a Law Pillar, and an Ethics Pillar—the three key pillars of decision making in business and in life—the model enables you to achieve the twin goals that lead to business success: managing risk and creating value.

Book Interpretable Machine Learning

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Book Machine Learning with Swift

Download or read book Machine Learning with Swift written by Oleksandr Sosnovshchenko and published by Packt Publishing Ltd. This book was released on 2018-02-28 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease Key Features Implement effective machine learning solutions for your iOS applications Use Swift and Core ML to build and deploy popular machine learning models Develop neural networks for natural language processing and computer vision Book Description Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves. What you will learn Learn rapid model prototyping with Python and Swift Deploy pre-trained models to iOS using Core ML Find hidden patterns in the data using unsupervised learning Get a deeper understanding of the clustering techniques Learn modern compact architectures of neural networks for iOS devices Train neural networks for image processing and natural language processing Who this book is for iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book.

Book The Great Mental Models  Volume 1

Download or read book The Great Mental Models Volume 1 written by Shane Parrish and published by Penguin. This book was released on 2024-10-15 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage.