Use Known Groups in High-Dimensional Data to Derive Scores for Plots

accTrainTest | Two subsets of data each take in turn the role of test set |

aovFbyrow | calculate aov F-statistic for each row of a matrix |

cvdisc | Cross-validated accuracy, in linear discriminant calculations |

cvscores | For high-dimensional data with known groups, derive scores... |

defectiveCVdisc | defective accuracy assessments from linear discriminant... |

divideUp | Partition data into mutiple nearly equal subsets |

Golub | Golub data (7129 rows by 72 columns), after normalization |

golubInfo | Classifying factors for the 72 columns of the Golub data set |

hddplot.package | Use Known Groups in High-Dimensional Data to Derive Scores... |

orderFeatures | Order features, based on their ability to discriminate |

pcp | convenience version of the singular value decomposition |

plotTrainTest | Plot predictions for both a I/II train/test split, and the... |

qqthin | a version of qqplot() that thins out points that overplot |

scoreplot | Plot discriminant function scores, with various... |

simulateScores | Generate linear discriminant scores from random data, after... |

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