ADaM: a data mining toolkit for scientists and engineers. Algorithm Development and Mining (ADaM) is a data mining toolkit designed for use with scientific data. It provides classification, clustering and association rule mining methods that are common to many data mining systems. In addition, it provides feature reduction capabilities, image processing, data cleaning and preprocessing capabilities that are of value when mining scientific data. The toolkit is packaged as a suite of independent components, which are designed to work in grid and cluster environments. The toolkit is extensible and scalable, and has been successfully used in several diverse data mining applications. ADaM has also been used in conjunction with other data mining toolkits and with point tools. This paper presents the architecture and design of the ADaM toolkit and discusses its application in detecting cumulus cloud fields in satellite imagery.

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  1. Alcalá-Fdez, J.; Sánchez, L.; García, S.; del Jesus, M. J.; Ventura, S.; Garrell, J. M.; Otero, J.; Romero, C.; Bacardit, J.; Rivas, V. M.; Fernández, J. C.; Herrera, F.: KEEL: a software tool to assess evolutionary algorithms for data mining problems (2009) ioport