Adjusted sparse linear programming method for classifying multi-dimensional biological data
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United States of America Patent
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Dec 16, 2008
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Jul 12, 2007
app pub date -
Jan 12, 2006
filing date -
Jan 12, 2006
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Abstract
The invention relates to improved methods and computer-based systems and software products useful for deriving and optimizing linear classifiers based on an adjusted sparse linear programming methodology (A-SPLP). This methodology is based on minimizing an objective function, wherein the objective function includes a loss term representing the performance of the objective function on a training dataset comprising at least two separate, adjustable weighting constants associated with classification errors for data points in-class and not-in-class, respectively.
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