Exploratory Data Mining and Data Cleaning
Aus der Reihe
Wiley Series in Probability and Statistics
134,99 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
01.08.2003
Verlag
WileySeitenzahl
204 (Printausgabe)
Dateigröße
1322 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9780471458647
* Written for practitioners of data mining, data cleaning and
database management.
* Presents a technical treatment of data quality including
process, metrics, tools and algorithms.
* Focuses on developing an evolving modeling strategy through an
iterative data exploration loop and incorporation of domain
knowledge.
* Addresses methods of detecting, quantifying and correcting data
quality issues that can have a significant impact on findings and
decisions, using commercially available tools as well as new
algorithmic approaches.
* Uses case studies to illustrate applications in real life
scenarios.
* Highlights new approaches and methodologies, such as the
DataSphere space partitioning and summary based analysis
techniques.
Exploratory Data Mining and Data Cleaning will serve as an
important reference for serious data analysts who need to analyze
large amounts of unfamiliar data, managers of operations databases,
and students in undergraduate or graduate level courses dealing
with large scale data analys is and data mining.
database management.
* Presents a technical treatment of data quality including
process, metrics, tools and algorithms.
* Focuses on developing an evolving modeling strategy through an
iterative data exploration loop and incorporation of domain
knowledge.
* Addresses methods of detecting, quantifying and correcting data
quality issues that can have a significant impact on findings and
decisions, using commercially available tools as well as new
algorithmic approaches.
* Uses case studies to illustrate applications in real life
scenarios.
* Highlights new approaches and methodologies, such as the
DataSphere space partitioning and summary based analysis
techniques.
Exploratory Data Mining and Data Cleaning will serve as an
important reference for serious data analysts who need to analyze
large amounts of unfamiliar data, managers of operations databases,
and students in undergraduate or graduate level courses dealing
with large scale data analys is and data mining.
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