Friday, June 22, 2007

Quantoids corner - ROC curve classification

For my fellow quantoids.

A frequent statistical problem faced by us who do research in intelligence theory/testing is how to quantify the accuracy (sensitivity/specificity) of classification from a test score (or collection of test scores). Over the past years I've seen more-and-more published on the use of ROC curves (receiver operating characteristic curves) for evaluation classification accuracy. Typically the readings have been technical in nature. Just this week the Data Mining in MATLAB blog posted a GREAT "ROC for dummies" explanation. I loved it. It explains this procedure in very simple language. Take a peak if you are doing classification research and/or if you find yourself reading articles that use ROC methods.

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