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Book Review: Discovering Knowledge in Data - An Introduction to Data Mining

Learn Data Mining by doing data mining

Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets. Employing a "white box" methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms and statistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include:

  • Data preprocessing and classification
  • Exploratory analysis
  • Decision trees
  • Neural and Kohonen networks
  • Hierarchical and k-means clustering
  • Association rules
  • Model evaluation techniques
Complete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge.
Data Mining Machine Learning Analytics Quant Statistics Econometrics Biostatistics Web Analytics Business Intelligence Risk Management Operations Research AI Predictive Modeling Actuarial Sciences Statistical Programming Customer Insight Data Modeling Competitive Intelligence Market Research Information Retrieval Computer Science Retail Analytics Healthcare Analytics ROI Optimization Design Of Experiments Scoring Models Six Sigma SAS Splus SAP ETL SPSS CRM Cloud Computing Electrical Engineering Fraud Detection Marketing Databases Data Analysis Decision Science Text Mining