Han Cao1, Jiayu Zhou2, Emanuel Schwarz1. 1. Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. 2. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA.
Abstract
MOTIVATION: Multi-task learning (MTL) is a machine learning technique for simultaneous learning of multiple related classification or regression tasks. Despite its increasing popularity, MTL algorithms are currently not available in the widely used software environment R, creating a bottleneck for their application in biomedical research. RESULTS: We developed an efficient, easy-to-use R library for MTL (www.r-project.org) comprising 10 algorithms applicable for regression, classification, joint predictor selection, task clustering, low-rank learning and incorporation of biological networks. We demonstrate the utility of the algorithms using simulated data. AVAILABILITY AND IMPLEMENTATION: The RMTL package is an open source R package and is freely available at https://github.com/transbioZI/RMTL. RMTL will also be available on cran.r-project.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Multi-task learning (MTL) is a machine learning technique for simultaneous learning of multiple related classification or regression tasks. Despite its increasing popularity, MTL algorithms are currently not available in the widely used software environment R, creating a bottleneck for their application in biomedical research. RESULTS: We developed an efficient, easy-to-use R library for MTL (www.r-project.org) comprising 10 algorithms applicable for regression, classification, joint predictor selection, task clustering, low-rank learning and incorporation of biological networks. We demonstrate the utility of the algorithms using simulated data. AVAILABILITY AND IMPLEMENTATION: The RMTL package is an open source R package and is freely available at https://github.com/transbioZI/RMTL. RMTL will also be available on cran.r-project.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Davide De Francesco; Yair J Blumenfeld; Ivana Marić; Jonathan A Mayo; Alan L Chang; Ramin Fallahzadeh; Thanaphong Phongpreecha; Alex J Butwick; Maria Xenochristou; Ciaran S Phibbs; Neda H Bidoki; Martin Becker; Anthony Culos; Camilo Espinosa; Qun Liu; Karl G Sylvester; Brice Gaudilliere; Martin S Angst; David K Stevenson; Gary M Shaw; Nima Aghaeepour Journal: iScience Date: 2022-03-22