Description Usage Arguments Details Author(s)

View source: R/BOSO_multiple_ColdStart.R

Bonjour

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ```
BOSO.single(
x,
y,
xval,
yval,
nlambda = 100,
lambda.min.ratio = ifelse(nrow(x) < ncol(x), 0.01, 1e-04),
lambda = NULL,
intercept = TRUE,
standardize = TRUE,
dfmin = 0,
dfmax = NULL,
costErrorVal = 1,
costErrorTrain = 0,
costVars = 0,
Threads = 0,
timeLimit = 1e+75
)
``` |

`x` |
Input matrix, of dimension 'n' x 'p'. This is the data from the training partition. Its recommended to be class "matrix". |

`y` |
Response variable for the training dataset. A matrix of one column or a vector, with 'n' elements |

`xval` |
Input matrix, of dimension 'n' x 'p'. This is the data from the validation partition. Its recommended to be class "matrix". |

`yval` |
Response variable for the validation dataset. A matrix of one column or a vector, with 'n' elements |

`nlambda` |
The number of lambda values. Default is 100. |

`lambda.min.ratio` |
Smallest value for lambda, as a fraction of lambda.max, the (data derived) entry value |

`lambda` |
A user supplied lambda sequence. Typical usage is to have the program compute its own lambda sequence based on nlambda and lambda.min.ratio. Supplying a value of lambda overrides this. WARNING: use with care |

`intercept` |
Boolean variable to indicate if intercept should be added or not. Default is false. |

`standardize` |
Boolean variable to indicate if data should be scaled according to mean(x) mean(y) and sd(x) or not. Default is false. |

`dfmin` |
Minimum number of variables to be included in the problem. The intercept is not included in this number. Default is 0. |

`dfmax` |
Maximum number of variables to be included in the problem. The intercept is not included in this number. Default is min(p,n). |

`costErrorVal` |
Cost of error of the validation set in the objective function. Default is 1. WARNING: use with care, changing this value changes the formulation presented in the main article. |

`costErrorTrain` |
Cost of error of the training set in the objective function. Default is 0. WARNING: use with care, changing this value changes the formulation presented in the main article. |

`costVars` |
Cost of new variables in the objective function. Default is 0. WARNING: use with care, changing this value changes the formulation presented in the main article. |

`Threads` |
CPLEX parameter, number of cores that cplex is allowed to use. Default is 0 (automatic). |

`timeLimit` |
CPLEX parameter, time limit per problem provided to CPLEX. Default is 1e75 (infinite time). |

Compute the BOSO for ust one block. This function calls ILOG IBM CPLEX with cplexAPI to solve the optimization problem

Luis V. Valcarcel

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