Imbalanced data classification using MapReduce and relief - Joanna Jedrzejowicz; Robert Kostrzewski; Jakub Neumann; Magdalena Zakrzewska (Journal of Information and Telecommunication, 2018)
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.