Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Oversampling for Imbalanced Learning Based on K-Means and SMOTE   Learning from class-imbalanced data continues to be a common and challenging
problem in supervised learning as standard classification algorithms are
designed to handle balanced class distributions. While different strategies
exist to tackle this problem, methods which generate artificial data to achieve
a balanced class distribution are more versatile than modifications to the
classification algorithm. Such techniques, called oversamplers, modify the
training data, allowing any classifier to be used with class-imbalanced
datasets. Many algorithms have been proposed for this task, but most are
complex and tend to generate unnecessary noise. This work presents a simple and
effective oversampling method based on k-means clustering and SMOTE
oversampling, which avoids the generation of noise and effectively overcomes
imbalances between and within classes. Empirical results of extensive
experiments with 71 datasets show that training data oversampled with the
proposed method improves classification results. Moreover, k-means SMOTE
consistently outperforms other popular oversampling methods. An implementation
is made available in the python programming language.

25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
33
The categories of this paper are: plasm-ph
29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph