Languages - Quick Fix Go Pubmed [citation needed]» Blog Archive » large-scale data exploration, MIC-style UPDATE 2/8/2012: Simon & Tibshirani posted a critical commentary on this paper here. See additional thoughts here. Real-world data are messy. Relationships between two variables can take on an infinite number of forms, and while one doesn’t see, say, umbrella-shaped data very often, strange things can happen. When scientists talk about correlations or associations between variables, they’re usually referring to one very specific form of relationship–namely, a linear one. Detecting a non-linear association is potentially just as easy as detecting a linear relationship if we know the form of that association up front. A new paper in Science by David Reshef and colleagues (and as a friend pointed out, it’s a feat in and of itself just to get a statistics paper into Science) directly targets this data mining problem by introducing an elegant new measure of association called the Maximal Information Coefficient (MIC; see also the authors’ project website).
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Deja vu: Medline duplicate pubs database Deja Vu: a Database of Highly Similar Citations* Click this link to begin browsing entries , or click the "Browse" button above and follow the instructions. To access the entries discovered by the SIP method, click SIP entries We value your feedback. Join the discussion of scientific publication ethics on COPE. Deja vu is a database of extremely similar Medline citations. In the scientific research community plagiarism and multiple publications of the same data are considered unacceptable practices and can result in tremendous misunderstanding and waste of time and energy. The application of text similarity searching can robustly detect highly similar text records, offering a new tool for ensuring integrity in scientific publications. *There are many definitions of the terms "duplicate publications" and "plagiarism", and the characterization of a citation or document is subjective. Disclaimer Latest News 2009-11-09 - Deja vu update Deja vu database has recently been updated.