Data Mining and Knowledge Discovery Handbook [E-Book] / edited by Oded Maimon, Lior Rokach.
Maimon, Oded, (editor)
Rokach, Lior, (editor)
2.
Boston, MA : Springer, 2010
XX, 1285 p. 40 illus. online resource.
englisch
9780387098234
10.1007/978-0-387-09823-4
Full Text
Table of Contents:
  • to Knowledge Discovery and Data Mining
  • Preprocessing Methods
  • Data Cleansing: A Prelude to Knowledge Discovery
  • Handling Missing Attribute Values
  • Geometric Methods for Feature Extraction and Dimensional Reduction - A Guided Tour
  • Dimension Reduction and Feature Selection
  • Discretization Methods
  • Outlier Detection
  • Supervised Methods
  • Supervised Learning
  • Classification Trees
  • Bayesian Networks
  • Data Mining within a Regression Framework
  • Support Vector Machines
  • Rule Induction
  • Unsupervised Methods
  • A survey of Clustering Algorithms
  • Association Rules
  • Frequent Set Mining
  • Constraint-based Data Mining
  • Link Analysis
  • Soft Computing Methods
  • A Review of Evolutionary Algorithms for Data Mining
  • A Review of Reinforcement Learning Methods
  • Neural Networks For Data Mining
  • Granular Computing and Rough Sets - An Incremental Development
  • Pattern Clustering Using a Swarm Intelligence Approach
  • Using Fuzzy Logic in Data Mining
  • Supporting Methods
  • Statistical Methods for Data Mining
  • Logics for Data Mining
  • Wavelet Methods in Data Mining
  • Fractal Mining - Self Similarity-based Clustering and its Applications
  • Visual Analysis of Sequences Using Fractal Geometry
  • Interestingness Measures - On Determining What Is Interesting
  • Quality Assessment Approaches in Data Mining
  • Data Mining Model Comparison
  • Data Mining Query Languages
  • Advanced Methods
  • Mining Multi-label Data
  • Privacy in Data Mining
  • Meta-Learning - Concepts and Techniques
  • Bias vs Variance Decomposition for Regression and Classification
  • Mining with Rare Cases
  • Data Stream Mining
  • Mining Concept-Drifting Data Streams
  • Mining High-Dimensional Data
  • Text Mining and Information Extraction
  • Spatial Data Mining
  • Spatio-temporal clustering
  • Data Mining for Imbalanced Datasets: An Overview
  • Relational Data Mining
  • Web Mining
  • A Review of Web Document Clustering Approaches
  • Causal Discovery
  • Ensemble Methods in Supervised Learning
  • Data Mining using Decomposition Methods
  • Information Fusion - Methods and Aggregation Operators
  • Parallel and Grid-Based Data Mining – Algorithms, Models and Systems for High-Performance KDD
  • Collaborative Data Mining
  • Organizational Data Mining
  • Mining Time Series Data
  • Applications
  • Multimedia Data Mining
  • Data Mining in Medicine
  • Learning Information Patterns in Biological Databases - Stochastic Data Mining
  • Data Mining for Financial Applications
  • Data Mining for Intrusion Detection
  • Data Mining for CRM
  • Data Mining for Target Marketing
  • NHECD - Nano Health and Environmental Commented Database
  • Software
  • Commercial Data Mining Software
  • Weka-A Machine Learning Workbench for Data Mining.