Imbalanced data classification using MapReduce and relief

Joanna Jędrzejowicz , Robert Kostrzewski , Jakub Neumann , Magdalena Zakrzewska


Classification of imbalanced data has been reported to require modification of standard classification algorithms and lately has attracted a lot of attention due to practical applications in industry, banking and finance. The aim of the paper is to examine algorithms known from literature when two modifications are introduced: MapReduce to parallelize computations and Relief to select most valuable attributes. Both modifications are needed in Big Data area. Also two new algorithms are considered.
Author Joanna Jędrzejowicz (FMPI/II)
Joanna Jędrzejowicz,,
- Institute of Informatics
, Robert Kostrzewski (FMPI)
Robert Kostrzewski,,
- Faculty of Mathematics, Physics and Informatics
, Jakub Neumann (FMPI/II)
Jakub Neumann,,
- Institute of Informatics
, Magdalena Zakrzewska (FMPI/II)
Magdalena Zakrzewska,,
- Institute of Informatics
Journal seriesJournal of Information and Telecommunication, ISSN 2475-1839, e-ISSN 2475-1847, (0 pkt)
Issue year2018
Publication size in sheets0.65
Keywords in Englishimbalanced data, classification, parallelization, feature selection
Languageen angielski
LicenseJournal (articles only); published final; Uznanie Autorstwa (CC-BY); with publication
Score (nominal)5
Score sourcejournalList
ScoreMinisterial score = 5.0, 03-02-2020, ArticleFromJournal
Citation count*3 (2020-07-08)
Share Share

Get link to the record

* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
Are you sure?