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Found 3 papers, 1 papers with code
Feature-weighted elastic net: using "features of features" for better prediction
In some supervised learning settings, the practitioner might have additional information on the features used for prediction.
Reluctant generalized additive modeling
Sparse generalized additive models (GAMs) are an extension of sparse generalized linear models which allow a model's prediction to vary non-linearly with an input variable.
Principal component-guided sparse regression
We propose a new method for supervised learning, especially suited to wide data where the number of features is much greater than the number of observations.
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