Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Machine Learning Based Ensemble Method for Automatic Multiclass
  Classification of Decisions   Stakeholders make various types of decisions with respect to requirements,
design, management, and so on during the software development life cycle.
Nevertheless, these decisions are typically not well documented and classified
due to limited human resources, time, and budget. To this end, automatic
approaches provide a promising way. In this paper, we aimed at automatically
classifying decisions into five types to help stakeholders better document and
understand decisions. First, we collected a dataset from the Hibernate
developer mailing list. We then experimented and evaluated 270 configurations
regarding feature selection, feature extraction techniques, and machine
learning classifiers to seek the best configuration for classifying decisions.
Especially, we applied an ensemble learning method and constructed ensemble
classifiers to compare the performance between ensemble classifiers and base
classifiers. Our experiment results show that (1) feature selection can
decently improve the classification results; (2) ensemble classifiers can
outperform base classifiers provided that ensemble classifiers are well
constructed; (3) BoW + 50% features selected by feature selection with an
ensemble classifier that combines Na\"ive Bayes (NB), Logistic Regression (LR),
and Support Vector Machine (SVM) achieves the best classification result (with
a weighted precision of 0.750, a weighted recall of 0.739, and a weighted
F1-score of 0.727) among all the configurations. Our work can benefit various
types of stakeholders in software development through providing an automatic
approach for effectively classifying decisions into specific types that are
relevant to their interests.

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The categories of this paper are: gr-qc
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The categories of this paper are: mtrl-th
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The categories of this paper are: nlin
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The categories of this paper are: chao-dyn
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The categories of this paper are: ao-sci
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The categories of this paper are: math
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-th
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The categories of this paper are: funct-an
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The categories of this paper are: dg-ga
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The categories of this paper are: quant-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: solv-int
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The categories of this paper are: alg-geom
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The categories of this paper are: stat
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The categories of this paper are: astro-ph