Spectral feature selection for data mining /

Spremljeno u:

Bibliografski detalji
Glavni autori:	Zhao, Zheng (Zheng Alan) (Autor), Liu, Huan, 1958- (Autor)
Format:	Elektronički e-knjiga
Jezik:	engleski
Izdano:	Boca Raton, FL : CRC Press, [2012]
Serija:	Chapman & Hall/CRC data mining and knowledge discovery series.
Teme:	Data mining. Electronic books.
Online pristup:	Click to View
Oznake:	Dodaj oznaku Bez oznaka, Budi prvi tko označuje ovaj zapis!

Slični predmeti: Spectral feature selection for data mining /

Quick Look
Data mining concepts and techniques /
Quick Look
Data analysis and data mining an introduction /
Quick Look
Data mining for dummies /
Quick Look
Data mining practical machine learning tools and techniques /
Quick Look
Active mining new directions of data mining /
Quick Look
Data mining and management
Quick Look
Data mining practical machine learning tools and techniques /
Quick Look
Data mining and predictive analytics /
Quick Look
Data mining applications with R /
Quick Look
Data mining in time series databases
Quick Look
Data mining and statistics for decision making
Quick Look
Discovering knowledge in data an introduction to data mining /
Quick Look
Practical text mining and statistical analysis for non-structured text data applications
Quick Look
Predictive analytics and data mining : concepts and practice with rapidminer /
Quick Look
Visual data mining the VisMiner approach /
Quick Look
Data mining algorithms : explained using R /
Quick Look
Business analytics and data mining with R
Quick Look
Sports Data Mining
Quick Look
Social media mining with R : deploy cutting-edge sentiment analysis techniques to real-world social media data using R /
Quick Look
Statistical data analytics : foundations for data mining, informatics, and knowledge discovery /
Quick Look
Data smart : using data science to transform information into insight /
Quick Look
Making sense of data III a practical guide to designing interactive data visualizations /
Quick Look
Text mining applications and theory /
Quick Look
Taming the big data tidal wave finding opportunities in huge data streams with advanced analytics /