Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fast SVM-based Feature Elimination Utilizing Data Radius, Hard-Margin,
  Soft-Margin   Margin maximization in the hard-margin sense, proposed as feature elimination
criterion by the MFE-LO method, is combined here with data radius utilization
to further aim to lower generalization error, as several published bounds and
bound-related formulations pertaining to lowering misclassification risk (or
error) pertain to radius e.g. product of squared radius and weight vector
squared norm. Additionally, we propose additional novel feature elimination
criteria that, while instead being in the soft-margin sense, too can utilize
data radius, utilizing previously published bound-related formulations for
approaching radius for the soft-margin sense, whereby e.g. a focus was on the
principle stated therein as "finding a bound whose minima are in a region with
small leave-one-out values may be more important than its tightness". These
additional criteria we propose combine radius utilization with a novel and
computationally low-cost soft-margin light classifier retraining approach we
devise named QP1; QP1 is the soft-margin alternative to the hard-margin LO. We
correct an error in the MFE-LO description, find MFE-LO achieves the highest
generalization accuracy among the previously published margin-based feature
elimination (MFE) methods, discuss some limitations of MFE-LO, and find our
novel methods herein outperform MFE-LO, attain lower test set classification
error rate. On several datasets that each both have a large number of features
and fall into the `large features few samples' dataset category, and on
datasets with lower (low-to-intermediate) number of features, our novel methods
give promising results. Especially, among our methods the tunable ones, that do
not employ (the non-tunable) LO approach, can be tuned more aggressively in the
future than herein, to aim to demonstrate for them even higher performance than
herein.

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The categories of this paper are: quant-ph
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
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The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
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The categories of this paper are: dg-ga
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The categories of this paper are: math-ph
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The categories of this paper are: solv-int
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The categories of this paper are: q-alg
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The categories of this paper are: hep-lat
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The categories of this paper are: supr-con
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The categories of this paper are: acc-phys
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The categories of this paper are: mtrl-th
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The categories of this paper are: physics
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The categories of this paper are: cond-mat