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Found 3 papers, 2 papers with code
Knowledge-Guided Additive Modeling For Supervised Regression
Learning processes by exploiting restricted domain knowledge is an important task across a plethora of scientific areas, with more and more hybrid methods combining data-driven and model-based approaches.
Optimizing model-agnostic Random Subspace ensembles
The degree of randomization in our parametric Random Subspace is thus automatically tuned through the optimization of the feature selection probabilities.
Context-dependent feature analysis with random forests
In many cases, feature selection is often more complicated than identifying a single subset of input variables that would together explain the output.
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