Saturday, 17-Nov-18, 1:20 PM
Welcome Guest

My Blog

Site menu
Login form
Section categories
Main » Files » My files

Encyclopedia of data warehousing and mining, Volume 1
[ Download from this server (37.1 Kb) · Download from mirror (13.15 MB) ] 21-Jan-12, 11:04 PM
Table of Contents:
Introduction :
Fundamentals of data mining, Data Mining Functionalities, Classification of Data Mining systems, Major issues in Data Mining. Data Preprocessing : Needs Preprocessing the Data, Data Cleaning, Data Integration and Transformation, Data Reduction, Discretization and Concept Hierarchy Generation.
Data Warehouse and OLAP Technology for Data Mining Data Warehouse, Multidimensional Data Model, Data Warehouse Architecture, Data Warehouse Implementation,Further Development of Data Cube Technology, From Data Warehousing to Data Mining.
Data Mining Primitives, Languages, and System Architectures : Data Mining Primitives, Data Mining
Query Languages, Designing Graphical User Interfaces Based on a Data Mining Query Language
Architectures of Data Mining Systems.
Concepts Description : Characterization and Comparison : Data Generalization and Summarization-
Based Characterization, Analytical Characterization: Analysis of Attribute Relevance, Mining Class
Comparisons: Discriminating between Different Classes, Mining Descriptive Statistical Measures in Large Databases.
Mining Association Rules in Large Databases : Association Rule Mining, Mining Single-Dimensional
Boolean Association Rules from Transactional Databases, Mining Multilevel Association Rules from
Transaction Databases, Mining Multidimensional Association Rules from Relational Databases and Data Warehouses, From Association Mining to Correlation Analysis, Constraint-Based Association Mining.
Classification and Prediction : Issues Regarding Classification and Prediction, Classification by
Decision Tree Induction, Bayesian Classification, Classification by Backpropagation, Classification Based on Concepts from Association Rule Mining, Other Classification Methods, Prediction, Classifier Accuracy.
Cluster Analysis Introduction : Types of Data in Cluster Analysis, A Categorization of Major Clustering Methods, Partitioning Methods, Density-Based Methods, Grid-Based Methods, Model-Based Clustering Methods, Outlier Analysis.
Mining Complex Types of Data : Multimensional Analysis and Descriptive Mining of Complex, Data
Objects, Mining Spatial Databases, Mining Multimedia Databases, Mining Time-Series and Sequence Data, Mining Text Databases, Mining the World Wide Web.
Category: My files | Added by: mani
Views: 385 | Downloads: 159 | Comments: 1 | Rating: 0.0/0
Total comments: 0
Only registered users can add comments.
[ Registration | Login ]
Our poll
Rate my site
Total of answers: 11
Site friends

Total online: 1
Guests: 1
Users: 0