Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MEBoost: Mixing Estimators with Boosting for Imbalanced Data
  Classification   Class imbalance problem has been a challenging research problem in the fields
of machine learning and data mining as most real life datasets are imbalanced.
Several existing machine learning algorithms try to maximize the accuracy
classification by correctly identifying majority class samples while ignoring
the minority class. However, the concept of the minority class instances
usually represents a higher interest than the majority class. Recently, several
cost sensitive methods, ensemble models and sampling techniques have been used
in literature in order to classify imbalance datasets. In this paper, we
propose MEBoost, a new boosting algorithm for imbalanced datasets. MEBoost
mixes two different weak learners with boosting to improve the performance on
imbalanced datasets. MEBoost is an alternative to the existing techniques such
as SMOTEBoost, RUSBoost, Adaboost, etc. The performance of MEBoost has been
evaluated on 12 benchmark imbalanced datasets with state of the art ensemble
methods like SMOTEBoost, RUSBoost, Easy Ensemble, EUSBoost, DataBoost.
Experimental results show significant improvement over the other methods and it
can be concluded that MEBoost is an effective and promising algorithm to deal
with imbalance datasets. The python version of the code is available here:
https://github.com/farshidrayhanuiu/

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The categories of this paper are: math
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The categories of this paper are: supr-con
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: nucl-th
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The categories of this paper are: nlin
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The categories of this paper are: ao-sci
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The categories of this paper are: adap-org
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The categories of this paper are: acc-phys
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The categories of this paper are: cmp-lg
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The categories of this paper are: q-bio
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The categories of this paper are: hep-lat
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The categories of this paper are: dg-ga
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The categories of this paper are: mtrl-th
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The categories of this paper are: math-ph