Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fitting Prediction Rule Ensembles with R Package pre   Prediction rule ensembles (PREs) are sparse collections of rules, offering
highly interpretable regression and classification models. This paper presents
the R package pre, which derives PREs through the methodology of Friedman and
Popescu (2008). The implementation and functionality of package pre is
described and illustrated through application on a dataset on the prediction of
depression. Furthermore, accuracy and sparsity of PREs is compared with that of
single trees, random forest and lasso regression in four benchmark datasets.
Results indicate that pre derives ensembles with predictive accuracy comparable
to that of random forests, while using a smaller number of variables for
prediction.

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The categories of this paper are: econ
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The categories of this paper are: funct-an
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The categories of this paper are: gr-qc
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The categories of this paper are: dg-ga
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The categories of this paper are: cond-mat
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-ph
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The categories of this paper are: physics
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The categories of this paper are: ao-sci
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: comp-gas
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The categories of this paper are: alg-geom
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The categories of this paper are: hep-th
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The categories of this paper are: nucl-th
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The categories of this paper are: astro-ph