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weka.MultiClassClassifierUpdateable_SGD

Visibility: public Uploaded 27-12-2015 by Joaquin Vanschoren
Weka_3.7.13 127 runs

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Weka implementation of MultiClassClassifierUpdateable

W | weka.SGD(4) | Full name of base classifier. (default: weka.classifiers.functions.Logistic) |

-do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built (use with caution). | |

C | The epsilon threshold (epsilon-insenstive and Huber loss only, default = 1e-3) | |

E | The number of epochs to perform (batch learning only, default = 500) | |

F | Set the loss function to minimize. 0 = hinge loss (SVM), 1 = log loss (logistic regression), 2 = squared loss (regression), 3 = epsilon insensitive loss (regression), 4 = Huber loss (regression). (default = 0) | |

L | Use log loss decoding for random and exhaustive codes | |

M | Sets the method to use. Valid values are 0 (1-against-all), 1 (random codes), 2 (exhaustive code), and 3 (1-against-1). (default 0) | default: 0 |

N | Don't normalize the data | |

P | Use pairwise coupling (only has an effect for 1-against1) | |

R | Sets the multiplier when using random codes. (default 2.0) | default: 2.0 |

S | Random number seed. (default 1) | default: 1 |

W | Full name of base classifier. (default: weka.classifiers.functions.Logistic) | default: weka.classifiers.functions.SGD |

num-decimal-places | The number of decimal places for the output of numbers in the model (default 2). | |

output-debug-info | If set, classifier is run in debug mode and may output additional info to the console |

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