Data Mining Concepts And Techniques

Author: Jiawei Han
Publisher: Elsevier
ISBN: 0123814804
Size: 10.70 MB
Format: PDF, ePub
View: 63

Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Data Mining A Heuristic Approach

Author: Abbass, Hussein A.
Publisher: IGI Global
ISBN: 1591400112
Size: 15.13 MB
Format: PDF, ePub, Mobi
View: 91

Real life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solving methods are no longer capable of handling this level of complexity, heuristic search methods have attracted increasing attention in recent years for solving such problems. Inspired by nature, biology, statistical mechanics, physics and neuroscience, heuristics techniques are used to solve many problems where traditional methods have failed. Data Mining: A Heuristic Approach will be a repository for the applications of these techniques in the area of data mining.

Data Mining Techniques

Author: Michael J. A. Berry
Publisher: John Wiley & Sons
ISBN: 9780471470649
Size: 19.72 MB
Format: PDF, Docs
View: 80

Many companies have invested in building large databases and data warehouses capable of storing vast amounts of information. This book offers business, sales and marketing managers a practical guide to accessing such information.

Data Mining

Author: Jiawei Han
Publisher: Morgan Kaufmann
ISBN: 1558604898
Size: 18.56 MB
Format: PDF, Mobi
View: 82

Data warehouse and OLAP technology for data mining. Data preprocessing. Data mining primitives, languages, and system architecture. Concept description: characterization and comparison. Mining association rules in large databases. Classification and prediction. Cluster analysis. Mining complex types of data. Applications and trends in data mining. Appendix.

Principles Of Data Mining

Author: D. J. Hand
Publisher: MIT Press
ISBN: 026208290X
Size: 19.26 MB
Format: PDF, ePub, Mobi
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The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics.

Discovering Knowledge In Data

Author: Daniel T. Larose
Publisher: John Wiley & Sons
ISBN: 9781118873571
Size: 17.88 MB
Format: PDF
View: 21

The field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. Due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before. This book provides the tools needed to thrive in today’s big data world. The author demonstrates how to leverage a company’s existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. The reader will “learn data mining by doing data mining”. By adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, Discovering Knowledge in Data, Second Edition remains the eminent reference on data mining. The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis. Includes new chapters on Multivariate Statistics, Preparing to Model the Data, and Imputation of Missing Data, and an Appendix on Data Summarization and Visualization Offers extensive coverage of the R statistical programming language Contains 280 end-of-chapter exercises Includes a companion website for university instructors who adopt the book

Data Mining And Analysis

Author: Mohammed J. Zaki
Publisher: Cambridge University Press
ISBN: 9780521766333
Size: 14.53 MB
Format: PDF, ePub, Docs
View: 78

A comprehensive overview of data mining from an algorithmic perspective, integrating related concepts from machine learning and statistics.