The International Virtual Observatory will pose unprecedented problems to data mining. We shortly discuss the effectiveness of neural networks as aids to the decisional process of the astronomer, and present the AstroMining Package. This package was written in Matlab and C++ and provides an user friendly interactive platform for various data mining tasks. Two applications are also shortly outlined: the derivation of photometric redshifts for a subsample of objects extracted from the Sloan Digital Sky Survey Early Data Release, and the evaluation of systematic patterns in the telemetry data for the Telescopio Nazionale GalilEo (TNG).
DATA MINING OF LARGE ASTRONOMICAL DATABASE WITH NEURAL TOOLS / Longo, Giuseppe; C., Donalek; G., Raiconi; A., Staiano; R., Tagliaferri; F., Pasian; Sessa, Salvatore; R., Smareglia; A., Volpicelli. - STAMPA. - 4847:(2002), pp. 265-276. (Intervento presentato al convegno Astronomical Data Analysis II tenutosi a Waikoloa nel 27-28/8/2002) [10.1117/12.461147].
DATA MINING OF LARGE ASTRONOMICAL DATABASE WITH NEURAL TOOLS
LONGO, GIUSEPPE;SESSA, SALVATORE;
2002
Abstract
The International Virtual Observatory will pose unprecedented problems to data mining. We shortly discuss the effectiveness of neural networks as aids to the decisional process of the astronomer, and present the AstroMining Package. This package was written in Matlab and C++ and provides an user friendly interactive platform for various data mining tasks. Two applications are also shortly outlined: the derivation of photometric redshifts for a subsample of objects extracted from the Sloan Digital Sky Survey Early Data Release, and the evaluation of systematic patterns in the telemetry data for the Telescopio Nazionale GalilEo (TNG).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.