Predicting Categorical and Continuous Outcomes Using One in Ten Rule

AUC | Area Under the Curve |

av_out | Averaging out the predictive power |

comb | Combining in a list |

compute_max_length | Maximum number of the regressions |

compute_max_weight | Maximum feasible weight of the predictors |

compute_weights | Weights of predictors |

cross_val | Cross-validation run |

cub | Three-way interactions and squares |

find_int | Finding the interacting terms based on the index |

find_sub | Finds certain subsets of predictors |

get_indices | Best regression |

get_predictions | Predictions for multinomial regression |

get_predictions_lin | Predictions for linear regression |

get_probabilities | Probabilities for multinomial regression |

make_numeric | Turning a non-numeric variable into a numeric one |

make_numeric_sets | Transforming the set of predictors into a numeric set |

quadr | Pairwise interactions and squares |

regr_ind | Indices of the best regressions |

sum_weights_sub | Cumulative weights of the predictors' subsets |

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