ML-flex: a flexible toolbox for performing classification analyses in parallel. (English) Zbl 1283.68298

Piccolo, Stephen R.; Frey, Lewis J.

J. Mach. Learn. Res. 13, 555-559 (2012).

Summary: Motivated by a need to classify high-dimensional, heterogeneous data from the bioinformatics domain, we developed ML-Flex, a machine-learning toolbox that enables users to perform two-class and multi-class classification analyses in a systematic yet flexible manner. ML-Flex was written in Java but is capable of interfacing with third-party packages written in other programming languages. It can handle multiple input-data formats and supports a variety of customizations. ML-Flex provides implementations of various validation strategies, which can be executed in parallel across multiple computing cores, processors, and nodes. Additionally, ML-Flex supports aggregating evidence across multiple algorithms and data sets via ensemble learning. This open-source software package is freely available from http://mlflex.sourceforge.net.

MSC:

68T05

Learning and adaptive systems in artificial intelligence

Keywords:

toolbox; classification; parallel; ensemble; reproducible research

Software:

C50; caret; KNIME; ML-flex; Orange; R; SHOGUN; Waffles; WEKA