A user-friendly multi-blocks analysis (Regularized Generalized Canonical Correlation Analysis, RGCCA) with all default settings predefined. Produce several plots to help clinicians to identify fingerprint: samples and variables projected on the two first component of the multi-block analysis, the 100 best predictors and the explained variance in the model.
|Author||Etienne Camenen, Arthur Tenenhaus and Vincent Guillemot|
|Maintainer||Arthur Tenenhaus <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on GitHub|
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