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  "Description": "Performs classification and variable selection on\nhigh-dimensional tensors (multi-dimensional arrays) after\nadjusting for additional covariates (scalar or vectors) as\nCATCH model in Pan, Mai and Zhang (2018) <arXiv:1805.04421>.\nThe low-dimensional covariates and the high-dimensional tensors\nare jointly modeled to predict a categorical outcome in a\nmulti-class discriminant analysis setting. The\nCovariate-Adjusted Tensor Classification in High-dimensions\n(CATCH) model is fitted in two steps: (1) adjust for the\ncovariates within each class; and (2) penalized estimation with\nthe adjusted tensor using a cyclic block coordinate descent\nalgorithm. The package can provide a solution path for tuning\nparameter in the penalized estimation step. Special case of the\nCATCH model includes linear discriminant analysis model and\nmatrix (or tensor) discriminant analysis without covariates.",
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