Description Usage Arguments Details Value

For a given data set, we apply cross-validation (cv) to select the optimal HDRDA tuning parameters.

1 2 |

`x` |
matrix containing the training data. The rows are the sample observations, and the columns are the features. |

`y` |
vector of class labels for each training observation |

`num_folds` |
the number of cross-validation folds. |

`num_lambda` |
The number of values of |

`num_gamma` |
The number of values of |

`shrinkage_type` |
the type of covariance-matrix shrinkage to apply. By
default, a ridge-like shrinkage is applied. If |

`verbose` |
If set to |

`...` |
Additional arguments passed to |

The number of cross-validation folds is given in `num_folds`

.

list containing the HDRDA model that minimizes cross-validation as
well as a `data.frame`

that summarizes the cross-validation results.

sparsediscrim documentation built on April 14, 2017, 12:25 p.m.

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