Desheng Wu Knihy

This book offers an overview of predictive methods using open-source software modeling with Rattle (R') and WEKA. It explores knowledge management, which integrates human knowledge with technological advancements and big data for data collection and analysis. The text categorizes analytic tools into three types: descriptive analytics, which report past events; predictive analytics, which utilize statistical and AI methods for forecasting and classification modeling; and prescriptive analytics, which employs quantitative models to optimize or improve systems. Data mining encompasses both descriptive and predictive modeling, while operations research includes all three types. The focus here is on prescriptive analytics, with simple explanations and demonstrations of descriptive tools. The second edition enhances examples of big data impact, updates visualization content, clarifies points, and expands on association rules and cluster analysis. Chapter 1 introduces knowledge management, while subsequent chapters cover basic data types, time series modeling, multiple regression, regression tree modeling, autoregressive/integrated/moving average models, GARCH models, and classification data mining tools, including support vector machines, random forests, and boosting. Business-related data is used for model demonstrations, and the book aims to explain methods descriptively, providing accessible datasets and software for readers.