Thresholded Partial Least Squares Model for Neuroimaging Data

Uses thresholded partial least squares algorithm to create a regression or classification model. For more information, see Lee, Bradlow, and Kable .

TPLSr 1.0.5

R Package for using Thresholded Partial Least Squares (TPLS) for big data regression and classification. It is developed with whole-brain neuroimaging (fMRI) MVPA predictors in mind. TPLS uses analytical calulations of partial least squares to dramatically speed-up the training of models with large number of features (~millions).

Citation: Lee, S., Bradlow, E. T., & Kable, J. W. (2022). Fast construction of interpretable whole-brain decoders. Cell Reports Methods. doi: https://doi.org/10.1016/j.crmeth.2022.100227

CRAN: https://CRAN.R-project.org/package=TPLSr
GITHUB: https://github.com/sangillee/TPLSr