Train deep neural networks for classification and regression

devianceBernoulli | Function to calculate deviance for model predictions assuming... |

devianceCategorical | Function to calculate deviance for model predictions assuming... |

devianceGamma | Function to calculate deviance for model predictions assuming... |

devianceNormal | Function to calculate deviance for model predictions assuming... |

deviancePoisson | Function to calculate deviance for model predictions assuming... |

devianceTweedie | Function to calculate deviance for model predictions assuming... |

dfBinary | Random data for binary classification example. |

dfGamma | Random data for Gamma distribution regression example. |

dfPoisson | Random data for Poisson process regression example. |

dfTweedie | Random data for compound Poisson-Gamma process regression... |

EdNetTrain | Train a neural network model |

normalise | Normalise a vector |

onehotEncode | One-hot encode a factor |

predictedClass | Converts class probabilities into a predicted class |

predict.EdNetModel | Predict for EdNetModel objects |

relu | Compute relu function on vector |

sigmoid | Compute sigmoid function on vector |

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