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OHPL: Ordered Homogeneity Pursuit Lasso
Ordered Homogeneity Pursuit Lasso (OHPL) is a variable selection method designed for high-dimensional data with strongly correlated variables.
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Vovk, Gammerman and Shafer "Algorithmic learning in a random world"
Algorithmic learning in a random world (Springer, New York, 2005) is a book about conformal prediction, a method that combines the power of modern machine learning, especially as applied to high-dimensional data sets, with the informative and valid measures of confidence.
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Teach Me | Responsive Learning Management System Template
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