Discovering Knowledge in Data

An Introduction to DATA MINING

Daniel T. Larose - Collection Wiley-Interscience

222 pages, parution le 29/12/2004

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Résumé

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.

L'auteur - Daniel T. Larose

Daniel T. Larose a obtenu son PHD en statistiques à l'université du Connecticut. Il est professeur de mathématiques et a été le fondateur et le directeur des programmes de Data Mining de la CCSU. Il est par ailleurs consultant en data science pour de grandes entreprises américaines.

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Sommaire

Preface
An Introduction to Data Mining
Data Preprocessing
Exploratory Data Analysis
Statistical Approaches to Estimation and Prediction
k-Nearest Neighbor
Decision Trees
Neural Networks
Hierarchical and k-Means Clustering
Kohonen networks
Association Rules
Model Evaluation Techniques
Epilogue: "We've Only Just Begun"
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Daniel T. Larose
Collection	Wiley-Interscience
Parution	29/12/2004
Nb. de pages	222
Format	16 x 24
Couverture	Relié
Poids	518g
Intérieur	Noir et Blanc
EAN13	9780471666578