Imbalanced data classification using MapReduce and relief
Joanna Jędrzejowicz , Robert Kostrzewski , Jakub Neumann , Magdalena Zakrzewska
AbstractClassification 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.
|Journal series||Journal of Information and Telecommunication, ISSN 2475-1839, e-ISSN 2475-1847, (0 pkt)|
|Publication size in sheets||0.65|
|Keywords in English||imbalanced data, classification, parallelization, feature selection|
|License||Journal (articles only); published final; ; with publication|
|Score||= 5.0, 03-02-2020, ArticleFromJournal|
|Citation count*||3 (2020-03-23)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.