Description Usage Arguments Value Examples

Training by using cross validation on a linear model with logistic loss and early stopping method. Return a list which contains the best iteration step, mean loss of training and validation data, and a predict function which gives a prediction based on the selected step.

1 2 | ```
LMLogisticLossEarlyStoppingCV(X.mat, y.vec, fold.vec = NULL,
max.iteration, step.size = 0.5)
``` |

`X.mat` |
train feature matrix of size [n x p] |

`y.vec` |
train label vector of size [n x 1] |

`fold.vec` |
fold index vector of size [n x 1] |

`max.iteration` |
integer scalar greater than 1 |

`step.size` |
a numeric scaler greater than 0, default is 0.5 |

result.list a list with mean.validation.loss.vec, mean.train.loss.vec,selected.steps,weight.vec,and predict function

1 2 3 4 5 |

SixianZhang/CS499-Coding-Project-2 documentation built on May 26, 2019, 3:31 p.m.

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