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A classification infrastructure built upon Discriminant Analysis has beendeveloped at NorthWest Research Associates for examining the statisticaldifferences between samples of two known populations. Originating to examinethe physical differences between flare-quiet and flare-imminent solar activeregions, we describe herein some details of the infrastructure including:parametrization of large datasets, schemes for handling "null" and "bad" datain multi-parameter analysis, application of non-parametric multi-dimensionalDiscriminant Analysis, an extension through Bayes' theorem to probabilisticclassification, and methods invoked for evaluating classifier success. Theclassifier infrastructure is applicable to a wide range of scientific questionsin solar physics. We demonstrate its application to the question ofdistinguishing flare-imminent from flare-quiet solar active regions, updatingresults from the original publications that were based on different data andmuch smaller sample sizes. Finally, as a demonstration of "Research toOperations" efforts in the space-weather forecasting context, we present theDiscriminant Analysis Flare Forecasting System (DAFFS), a near-real-timeoperationally-running solar flare forecasting tool that was developed from theresearch-directed infrastructure.

The NWRA Classification Infrastructure: Description and Extension to the Discriminant Analysis Flare Forecasting System (DAFFS)