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Data Mining Concepts, Models, Methods, and Algorithms

ISBN-10: 0471228524

ISBN-13: 9780471228523

Edition: 2003

Authors: Mehmed Kantardzic

List price: $111.00
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Description:

Data mining describes the often complex and sophisticated tools used in automatic data analysis such as analyzing a customer's previous buying habits Emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning Describes representative state-of-the-art methods and algorithms originating from different disciplines Offers guidance on how and when to use a particular software tool from among the hundreds offered when faced with a data set to mine A Wiley-IEEE Press Publication To view the solutions manual, visit ftp://ftp.wiley.com/public/sci_tech_med/data_mining/
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Book details

List price: $111.00
Copyright year: 2003
Publisher: John Wiley & Sons, Incorporated
Publication date: 10/25/2002
Binding: Paperback
Pages: 360
Size: 7.00" wide x 10.00" long x 0.75" tall
Weight: 1.342
Language: English

Preface
Data Mining Concepts
Introduction
Data-mining roots
Data-mining process
Large data sets
Data warehouses
Organization of this book
Review questions and problems
References for further study
Preparing the Data
Representation of raw data
Characteristics of raw data
Transformation of raw data
Missing data
Time-dependent data
Outlier analysis
Review questions and problems
References for further study
Data Reduction
Dimensions of large data sets
Features reduction
Entropy measure for ranking features
Principal component analysis
Values reduction
Feature discretization: ChiMerge technique
Cases reduction
Review questions and problems
References for further study
Learning from Data
Learning machine
Statistical learning theory
Types of learning methods
Common learning tasks
Model estimation
Review questions and problems
References for further study
Statistical Methods
Statistical inference
Assessing differences in data sets
Bayesian inference
Predictive regression
Analysis of variance
Logistic regression
Log-linear models
Linear discriminant analysis
Review questions and problems
References for further study
Cluster Analysis
Clustering concepts
Similarity measures
Agglomerative hierarchical clustering
Partitional clustering
Incremental clustering
Review questions and problems
References for further study
Decision Trees and Decision Rules
Decision trees
C4.5 Algorithm: generating a decision tree
Unknown attribute values
Pruning decision tree
C4.5 Algorithm: generating decision rules
Limitations of decision trees and decision rules
Associative-classification method
Review questions and problems
References for further study
Association Rules
Market-Basket Analysis
Algorithm Apriori
From frequent itemsets to association rules
Improving the efficiency of the Apriori algorithm
Frequent pattern-growth method
Multidimensional association-rules mining
Web mining
HITS and LOGSOM algorithms
Mining path-traversal patterns
Text mining
Review questions and problems
References for further study
Artificial Neural Networks
Model of an artificial neuron
Architectures of artificial neural networks
Learning process
Learning tasks
Multilayer perceptrons
Competitive networks and competitive learning
Review questions and problems
References for further study
Genetic Algorithms
Fundamentals of genetic algorithms
Optimization using genetic algorithms
A simple illustration of a genetic algorithm
Schemata
Traveling salesman problem
Machine learning using genetic algorithms
Review questions and problems
References for further study
Fuzzy Sets and Fuzzy Logic
Fuzzy sets
Fuzzy set operations
Extension principle and fuzzy relations
Fuzzy logic and fuzzy inference systems
Multifactorial evaluation
Extracting fuzzy models from data
Review questions and problems
References for further study
Visualization Methods
Perception and visualization
Scientific visualization and information visualization
Parallel coordinates
Radial visualization
Kohonen self-organized maps
Visualization systems for data mining
Review questions and problems
References for further study
References
Data-Mining Tools
Commercially and publicly available tools
Web site links
Data-Mining Applications
Data mining for financial data analysis
Data mining for the telecommunications industry
Data mining for the retail industry
Data mining in healthcare and biomedical research
Data mining in science and engineering
Pitfalls of data mining
Index
About the Author