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Single Index Models (SIMs) are simple yet flexible semi-parametric models for classification and regression. Response variables are modeled as a nonlinear, monotonic function of a linear combination of features. Estimation in this context requires learning both the feature weights, and the nonlinear function. While methods have been described to learn SIMs in the low dimensional regime, a metho...
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ژورنال
عنوان ژورنال: Journal of Multivariate Analysis
سال: 2015
ISSN: 0047-259X
DOI: 10.1016/j.jmva.2015.02.007