Concept description characterization and comparison

Dec 19, 2012Download as PPTX, PDF1 like3,055 views

Concept description involves data generalization and summarization to characterize concepts through analytical characterization of attribute relevance and mining descriptive statistical measures from large databases. It also allows for mining class comparisons to discriminate between different classes.

Concept Description: Characterization and
Comparison

• What is concept description?
• 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
• Summary

This document discusses dimensionality reduction techniques for data mining. It begins with an introduction to dimensionality reduction and reasons for using it. These include dealing with high-dimensional data issues like the curse of dimensionality. It then covers major dimensionality reduction techniques of feature selection and feature extraction. Feature selection techniques discussed include search strategies, feature ranking, and evaluation measures. Feature extraction maps data to a lower-dimensional space. The document outlines applications of dimensionality reduction like text mining and gene expression analysis. It concludes with trends in the field.

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1.8 discretizationKrish_ver2

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