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Knowledge Discovery and Data Mining Group

The basic problem in data mining is how to extract information from the huge amount of data that is amassed using computer technology. Inherently cross-disciplinary, data mining integrates theory and practice from statistics, mathematics, decision sciences, artificial and computation intelligence, and database management and then applies them to practical applciations in business, science and engineering. Rensselaer's Knowledge Discovery Data Mining Group intends to make Rensselaer a recognized leader in the industrial application of DM. Our goal is to build relationships with industry and government to gain expertise and visibility in the devlopment and use of our technologies on important data mining applications.

Nine Intel Pentium II 300MHz with MMX, 128MB RAM
One Intel Pentium II 266MHz with dual processor, 128MB RAM
One Intel Quad Pentium Pro 200 MHz, 1GB RAM
Intel Switchable hub.
All machines are running Windows NT on a local high-speed network.