Description Usage Arguments Author(s)

Some internal and under-development functions

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`m` |
Number of elements in a subset to be drawn. |

`p` |
Total number of available features. |

`mtry` |
Number of features to be drawn for each KNN. |

`eta` |
Coverage Probability. |

`nu` |
mean mutiplicity of a feature |

`rmax` |
number of series terms for independent geometric approximation |

`nsim` |
number of simulations for geometric simulation. |

`lambda` |
mean number of silient features. |

`samples` |
A vector of indice for a set of observations. |

`cl` |
A factor for classification labels. |

`train` |
A data matrix. |

`test` |
A data matrix. |

`y` |
A vector of responses. |

`k` |
Number of nearest neighbors. |

`cl` |
A vector of class labels. |

`K` |
Number of folds for cross-validation. |

`pk` |
A real number between 0 and to indicate the proportion of the feature set to be kept in each step. |

`r` |
Number of KNN to be generated. |

`seed` |
An integer seed. |

`criterion` |
either uses mean_accuracy or mean_support for best. |

`obj` |
A linear model. |

Shengqiao Li<[email protected]>

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