Introduction to Data Mining

Pang-Ning Tan, Michael Steinbach, Vipin Kumar

700 pages, parution le 25/07/2005

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Résumé

Introduction to Data Mining is a complète introduction to data mining for students, researchers, and professionals. It provides a sound understanding of the foundations of data mining, in addition to covering many important advanced topics.

Covers core data mining topics such as

Pre- and post-processing
Data exploration, including visualization and OLAP
Prédictive modeling
Association analysis
Clustering
Anomaly détection

Contains extensive figures and integrated examples

Requires a minimal mathematical background

Includes exercise solutions, links to data mining resources (e.g., data mining algorithms and data sets), and lecture slides

L'auteur - Vipin Kumar

Vipin Kumar is Professor m the Department of Computer Science and Engineering and the Director of the Army High Performance Computing Reseaich Center at the University of Minnesota. His research interests are in the areas of high performance computing, parallel algorithms (or scientific computing problems and data mining.

Sommaire

Introduction
Data
Exploring Data
Classification : Basic Concepts, Decision Trees, and Model Evaluation
Classification : Altenative Techniques
Association Analysis: Basic Concepts and Algorithms
Association Analysis: Advanced Concepts
Cluster analysis: Basic Concepts and Algorithms
Cluster analysis: Additional Issues and Algorithms
Anomaly Detection
A. Linear Algebra
B. Dimensionality Reduction
C. Probability and Statistics
D. Regression
E. Optimization

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Addison Wesley
Auteur(s)	Pang-Ning Tan, Michael Steinbach, Vipin Kumar
Parution	25/07/2005
Nb. de pages	700
Format	19,5 x 24
Couverture	Relié
Poids	1385g
Intérieur	Noir et Blanc
EAN13	9780321321367
ISBN13	978-0-321-32136-7