Uncertainty Handling and Quality Assessment in Data Mining

AvMichalis Vazirgiannis,Maria Halkidi

Häftad, Engelska, 2012

Del i serien Advanced Information and Knowledge Processing

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Beskrivning

The recent explosive growth of our ability to generate and store data has created a need for new, scalable and efficient, tools for data analysis.

Produktinformation

Utgivningsdatum:2012-10-04
Mått:155 x 235 x 13 mm
Vikt:350 g
Format:Häftad
Språk:Engelska
Serie:Advanced Information and Knowledge Processing
Antal sidor:226
Förlag:Springer London Ltd
ISBN:9781447111191

Utforska kategorier

Referensverk och tvärvetenskap inom Samhälle och politik
Databaser inom Data och IT
Hårdvara inom Data och IT

Innehållsförteckning

Data Mining Process.- 2.1 Introduction to the Main Concepts of Data Mining.- 2.2 Knowledge and Data Mining.- 2.3 The Data Mining Process.- 2.4 Classification of Data Mining Methods.- 2.5 Overview of Data Mining Tasks.- 2.6 Summary.- References.- Quality Assessment in Data Mining.- 3.1 Introduction.- 3.2 Data Pre-processing and Quality Assessment.- 3.3 Evaluation of Classification Methods.- 3.4 Association Rules.- 3.5 Cluster Validity.- 3.6 Summary.- References.- Uncertainty Handling in Data Mining.- 4.1 Introduction.- 4.2 Basic Concepts on Fuzzy Logic.- 4.3 Basic Concepts on Probabilistic Theory.- 4.4 Probabilistic and Fuzzy Approaches.- 4.5 The EM Algorithm.- 4.6 Fuzzy Cluster Analysis.- 4.7 Fuzzy Classification Approaches.- 4.8 Managing Uncertainty and Quality in the Classification Process.- 4.9 Fuzzy Association Rules.- 4.10 Summary.- References.- UMiner: A Data Mining System Handling Uncertainty and Quality.- 5.1 Introduction.- 5.2 UMiner Development Approach.- 5.3 System Architecture.- 5.4 UMiner’s Data Mining Tasks.- 5.5 Demonstration.- 5.6 Summary.- References.- Case Studies.- 6.1 Extracting Association Rules for Medical Data Analysis.- 6.2 The Mining Process.- 6.3 Cluster Analysis of Epidemiological Data.- References.

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