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fastPLS: Fast Partial Least Squares for High-Dimensional Data
Fast implementations of partial least squares models for high-dimensional regression and classification. The 'fastPLS' software provides compiled implementations of PLS-SVD, a SIMPLS-family estimator, OPLS and kernel PLS, together with truncated singular value decomposition backends, discriminant classifiers, cross-validation utilities and optional 'CUDA' or Apple 'Metal' acceleration when the required system libraries are available. Compact latent prediction and memory-aware numerical routes support analyses with large predictor or multivariate-response matrices.
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Package details |
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| Author | Stefano Cacciatore [aut, cre] (ORCID: <https://orcid.org/0000-0001-7052-7156>), Dupe Ojo [aut] (ORCID: <https://orcid.org/0000-0002-5301-8592>), Leonardo Tenori [aut] (ORCID: <https://orcid.org/0000-0001-6438-059X>), Alessia Vignoli [aut] (ORCID: <https://orcid.org/0000-0003-4038-6596>) |
| Bioconductor views | Classification DimensionReduction GPU GeneExpression GenePrediction Metabolomics Regression SingleCell Software |
| Maintainer | Stefano Cacciatore <tkcaccia@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.3 |
| URL | https://github.com/tkcaccia/fastPLS |
| Package repository | View on CRAN |
| Installation |
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