Download or read book Predictive Models to Risk Analysis With Neural Networks Regression and Decision Trees written by Scientific Books and published by Createspace Independent Publishing Platform. This book was released on 2016-01-01 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential aim of this book is to use predictive models to analyze risk. Models of decision trees, regression and neural networks are used to predict various risk categories. This book shows you how to build decision tree models to predict a categorical target and how to build regression tree models and neural network models to predict a continuous target. Successive chapters present examples that clarify the application of the models in the field of risk. The examples are solved step by step with SAS Enterprise Miner in order to make easier the understanding of the methodologies used. The book begins by introducing the basics of creating a project, manipulating data sources, and navigating through different results windows. Data Miming tools are used to build the main risk models: Decision Tree, Neural Network, and Regression. These are addressed in considerable detail, with numerous examples of practical business applications that are illustrated with tables, charts, displays, equations, and even manual calculations that let you see the essence of what Enterprise Miner is doing when it estimates or optimizes a given model.
Download or read book PREDICTIVE MODELS TO RISK ANALYSIS WITH NEURAL NETWORKS REGRESSION AND DECISION TREES written by and published by CESAR PEREZ. This book was released on with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential aim of this book is to use predictive models to analyze risk. Models of decision trees, regression and neural networks are used to predict various risk categories. This book shows you how to build decision tree models to predict a categorical target and how to build regression tree models and neural network models to predict a continuous target. Successive chapters present examples that clarify the application of the models in the field of risk. The examples are solved step by step with SAS Enterprise Miner in order to make easier the understanding of the methodologies used. The book begins by introducing the basics of creating a project, manipulating data sources, and navigating through different results windows. Data Mining tools are used to build the main risk models: Decision Tree, Neural Network, and Regression.
Download or read book Predictive Analytics using R written by Jeffrey Strickland and published by Lulu.com. This book was released on 2015-01-16 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about predictive analytics. Yet, each chapter could easily be handled by an entire volume of its own. So one might think of this a survey of predictive modeling. A predictive model is a statistical model or machine learning model used to predict future behavior based on past behavior. In order to use this book, one should have a basic understanding of mathematical statistics - it is an advanced book. Some theoretical foundations are laid out but not proven, but references are provided for additional coverage. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. You may download R, from a preferred CRAN mirror at http: //www.r-project.org/. The book is organized so that statistical models are presented first (hopefully in a logical order), followed by machine learning models, and then applications: uplift modeling and time series. One could use this a textbook with problem solving in R-but there are no "by-hand" exercises.
Download or read book Decision Trees Regression and Neural Network Models With Data Mining Tools written by Scientific Books and published by Createspace Independent Publishing Platform. This book was released on 2016-01-01 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book begins by introducing tools required for building predictive models. The aim is to build the three main predictive modeling tools: Decision Tree, Neural Network, and Regression. These are addressed in considerable detail, with numerous examples of practical business applications that are illustrated with tables, charts, displays, equations, and even manual calculations that let you see the essence of what Enterprise Miner is doing as it estimates or optimizes a given model.
Download or read book Predictive Modeling with SAS Enterprise Miner written by Kattamuri S. Sarma and published by SAS Institute. This book was released on 2017-07-20 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: « Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--
Download or read book AI Based Techniques for Predictive Modeling written by Kharade S K and published by . This book was released on 2023-05-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI-based techniques for predictive modeling involve using algorithms and machine learning techniques to analyze large amounts of data and identify patterns that can be used to predict future outcomes or trends. These techniques can be applied in a wide range of industries and applications, from finance and marketing to healthcare and manufacturing. One of the key advantages of AI-based predictive modeling is that it can identify patterns and trends that might not be immediately apparent to humans. These algorithms can analyze vast amounts of data from multiple sources, including historical data, real-time data, and external factors, to identify patterns and predict future outcomes with a high degree of accuracy. Some common techniques used in AI-based predictive modeling include decision trees, neural networks, and regression analysis. Decision trees are a type of algorithm that uses a hierarchical tree structure to identify patterns and relationships between variables. Neural networks, on the other hand, are modeled after the structure of the human brain and can identify complex patterns and relationships between variables. Regression analysis is another common technique used in predictive modeling that involves analyzing the relationship between two or more variables to predict future outcomes. This technique is often used in financial forecasting and risk analysis. Overall, AI-based techniques for predictive modeling offer significant benefits for businesses and organizations looking to make data-driven decisions. By analyzing large amounts of data and identifying patterns and trends, these techniques can help organizations predict future outcomes and make informed decisions that can improve efficiency, productivity, and profitability.
Download or read book Proceedings of the 7th International Conference on Economic Management and Green Development written by Xiaolong Li and published by Springer Nature. This book was released on with total page 2095 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Mining and Predictive Analytics written by Daniel T. Larose and published by John Wiley & Sons. This book was released on 2015-03-16 with total page 826 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
Download or read book Artificial Intelligence for Business Analytics written by Felix Weber and published by Springer Nature. This book was released on 2023-03-01 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: While methods of artificial intelligence (AI) were until a few years ago exclusively a topic of scientific discussions, today they are increasingly finding their way into products of everyday life. At the same time, the amount of data produced and available is growing due to increasing digitalization, the integration of digital measurement and control systems, and automatic exchange between devices (Internet of Things). In the future, the use of business intelligence (BI) and a look into the past will no longer be sufficient for most companies.Instead, business analytics, i.e., predictive and predictive analyses and automated decisions, will be needed to stay competitive in the future. The use of growing amounts of data is a significant challenge and one of the most important areas of data analysis is represented by artificial intelligence methods.This book provides a concise introduction to the essential aspects of using artificial intelligence methods for business analytics, presents machine learning and the most important algorithms in a comprehensible form using the business analytics technology framework, and shows application scenarios from various industries. In addition, it provides the Business Analytics Model for Artificial Intelligence, a reference procedure model for structuring BA and AI projects in the company. This book is a translation of the original German 1st edition Künstliche Intelligenz für Business Analytics by Felix Weber, published by Springer Fachmedien Wiesbaden GmbH, part of Springer Nature in 2020. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors.
Download or read book Intelligent Systems Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2018-06-04 with total page 2351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ongoing advancements in modern technology have led to significant developments in intelligent systems. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Intelligent Systems: Concepts, Methodologies, Tools, and Applications contains a compendium of the latest academic material on the latest breakthroughs and recent progress in intelligent systems. Including innovative studies on information retrieval, artificial intelligence, and software engineering, this multi-volume book is an ideal source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of intelligent systems.
Download or read book Risk Assessment and Financial Regulation in Emerging Markets Banking written by Alexander M. Karminsky and published by Springer Nature. This book was released on 2021-05-11 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes various approaches in modelling financial risks and compiling ratings. Focusing on emerging markets, it illustrates how risk assessment is performed and analyses the use of machine learning methods for financial risk assessment and measurement. It not only offers readers insights into the differences between emerging and developed markets, but also helps them understand the development of risk management approaches for banks. Highlighting current problems connected with the evaluation and modelling of financial risks in the banking sector of emerging markets, the book presents the methodologies applied to credit and market financial risks and integrated and payment risks, and discusses the outcomes. In addition it explores the systemic risks and innovations in banking and risk management by analyzing the features of risk measurement in emerging countries. Lastly, it demonstrates the aggregation of approaches to financial risk for emerging financial markets, comparing the experiences of various countries, including Russia, Belarus, China and Brazil.
Download or read book Audit Analytics in the Financial Industry written by Jun Dai and published by Emerald Group Publishing. This book was released on 2019-10-28 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Split into six parts, contributors explore ways to integrate Audit Analytics techniques into existing audit programs for the financial industry. Chapters include topics such as fraud risks in the credit card sector, clustering techniques, fraud and anomaly detection, and using Audit Analytics to assess risk in the lawsuit and payment processes.
Download or read book Big data analytics for smart healthcare applications written by Celestine Iwendi and published by Frontiers Media SA. This book was released on 2023-04-17 with total page 1365 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Geo information for Disaster Monitoring and Management written by Prem C. Pandey and published by Springer Nature. This book was released on with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Digital Human Modeling and Applications in Health Safety Ergonomics and Risk Management written by Vincent G. Duffy and published by Springer Nature. This book was released on with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Emerging Methods in Predictive Analytics Risk Management and Decision Making written by Hsu, William H. and published by IGI Global. This book was released on 2014-01-31 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision making tools are essential for the successful outcome of any organization. Recent advances in predictive analytics have aided in identifying particular points of leverage where critical decisions can be made. Emerging Methods in Predictive Analytics: Risk Management and Decision Making provides an interdisciplinary approach to predictive analytics; bringing together the fields of business, statistics, and information technology for effective decision making. Managers, business professionals, and decision makers in diverse fields will find the applications and cases presented in this text essential in providing new avenues for risk assessment, management, and predicting the future outcomes of their decisions.
Download or read book Safety Reliability and Risk Analysis written by R.D.J.M. Steenbergen and published by CRC Press. This book was released on 2013-09-18 with total page 3422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods of risk and reliability analysis are becoming increasingly important as decision support tools in various fields of engineering. Safety, Reliability and Risk Analysis: Beyond the Horizon covers a wide range of topics for which risk analysis forms an indispensable field of knowledge to ensure sufficient safety.
