Himalaya Data Mining Tools. With Himalaya Data Mining Tools we are developing new functionality for data mining and working on techniques to improve existing models. The long term goal of the project is to publish the source code of new cutting edge algorithms from the Cornell Database Group so that these new algorithms can be utilized and tested by other users in a structured environment. The initial release included two algorithms for mining patterns from itemsets in a transactional database. A new algorithm for regression tree construction has been recently posted. There are plans to include additional techniques such as data stream mining in the future. All algorithms are implemented in C++ and have been ported to both the Linux and Windows platforms. Extensive documentation is provided with Doxygen-generated HTML pages that detail all of the various components of both programs. This research has been supported by the National Science Foundation under Grants IIS-0084762 and IIS-0121175. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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References in zbMATH (referenced in 1 article )

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  1. Tsao, Wen-Kwang; Lee, Anthony J. T.; Liu, Ying-Ho; Chang, Ting-Wei; Lin, Hsiu-Hui: A data mining approach to face detection (2010)