DAMEWARE: A web cyberinfrastructure for astrophysical data mining
Massimo Brescia, Stefano Cavuoti, Giuseppe Longo, Alfonso Nocella,, Mauro Garofalo, Francesco Manna, Francesco Esposito, Giovanni Albano, Marisa, Guglielmo, Giovanni D'Angelo, Alessandro Di Guido, George S. Djorgovski, Ciro, Donalek, Ashish A. Mahabal, Matthew J. Graham

TL;DR
DAMEWARE is a web-based platform that enables astronomers to perform advanced data mining tasks on large, complex datasets, improving analysis of celestial objects and phenomena.
Contribution
It introduces a versatile, user-friendly web environment tailored for astronomical data mining, capable of handling high-dimensional data with minimal intervention.
Findings
Achieved better classification results than traditional methods.
Successfully applied to identify globular clusters and active galactic nuclei.
Enhanced photometric redshift estimation.
Abstract
Astronomy is undergoing through a methodological revolution triggered by an unprecedented wealth of complex and accurate data. The new panchromatic, synoptic sky surveys require advanced tools for discovering patterns and trends hidden behind data which are both complex and of high dimensionality. We present DAMEWARE (DAta Mining & Exploration Web Application REsource): a general purpose, web-based, distributed data mining environment developed for the exploration of large datasets, and finely tuned for astronomical applications. By means of graphical user interfaces, it allows the user to perform classification, regression or clustering tasks with machine learning methods. Salient features of DAMEWARE include its capability to work on large datasets with minimal human intervention, and to deal with a wide variety of real problems such as the classification of globular clusters in the…
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