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Data mining in space physics: MineTool algorithm
SciberQuest, Inc., Solana Beach, California, USA
SciberQuest, Inc., Solana Beach, California, USA
Department of Economics, University of California, San Diego, La Jolla, California, USA
Universidad Complutense de Madrid, Madrid, Spain
Institute of Space Science, National Central University, Jung-Li, Taiwan
Institute of Space Science, National Central University, Jung-Li, Taiwan
SciberQuest, Inc., Solana Beach, California, USA
San Diego Supercomputer Center, University of California, San Diego, La Jolla, California, USA
A novel data mining method called MineTool is introduced which, by virtue of automating the modeling process and model evaluations, makes it more accessible to nonexperts. The technique aggregates the various stages of model building into a four-step process consisting of (1) data segmentation and sampling, (2) variable preselection and transform generation, (3) predictive model estimation and validation, and (4) final model testing. Optimal strategies are chosen for each modeling step. However, the modular design of the MineTool enables the substitution of alternative strategies in any of the four modeling steps. A notable feature of the technique is that the final model is always in closed analytical form rather than “black box” form of most other techniques. MineTool can be used for analysis of data (e.g., time series) as well as images. The utility of the technique is illustrated through several examples based on synthetic data. Application of the technique to analysis of spacecraft data will be presented in subsequent papers.
Received 14 October 2006; accepted 2 August 2007; published 27 November 2007.
Citation: (2007), Data mining in space physics: MineTool algorithm, J. Geophys. Res., 112, A11215, doi:10.1029/2006JA012136.
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