Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Feature Selection with Conjunctions of Decision Stumps and Learning from
  Microarray Data   One of the objectives of designing feature selection learning algorithms is
to obtain classifiers that depend on a small number of attributes and have
verifiable future performance guarantees. There are few, if any, approaches
that successfully address the two goals simultaneously. Performance guarantees
become crucial for tasks such as microarray data analysis due to very small
sample sizes resulting in limited empirical evaluation. To the best of our
knowledge, such algorithms that give theoretical bounds on the future
performance have not been proposed so far in the context of the classification
of gene expression data. In this work, we investigate the premise of learning a
conjunction (or disjunction) of decision stumps in Occam's Razor, Sample
Compression, and PAC-Bayes learning settings for identifying a small subset of
attributes that can be used to perform reliable classification tasks. We apply
the proposed approaches for gene identification from DNA microarray data and
compare our results to those of well known successful approaches proposed for
the task. We show that our algorithm not only finds hypotheses with much
smaller number of genes while giving competitive classification accuracy but
also have tight risk guarantees on future performance unlike other approaches.
The proposed approaches are general and extensible in terms of both designing
novel algorithms and application to other domains.

18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
26
The categories of this paper are: bayes-an
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph