Description Usage Arguments Details Value Examples

This functions allows selection of variables from a feature table of discrete/categorial variables and a target class. The function is based on the algorithm described in Yu, L. and Liu, H.; Feature Selection for High-Dimensional Data A Fast Correlation Based Filter Solution, Proc. 20th Intl. Conf. Mach. Learn. (ICML-2003), Washington DC, 2003

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`x` |
A table of features (samples in rows, variables in columns, and each observation in each cell) |

`y` |
A target vector, factor containing classes of the observations. Note: the observations must be in the same order as the parameter x |

`thresh` |
A threshold for the minimum correlation (as determined by symettrical uncertainty) between each variable and the class. Defaults to 0.25. Note: this might drastically change the number of selected features. |

`n_genes` |
Sets the number of genes to be selected in the first part of the algorithm. If left unchanged, it defaults to NULL and the thresh parameter is used. Caution: it overrides the thresh parameter altogether. |

`verbose` |
Adds verbosity. Defaults to FALSE. |

`samples_in_rows` |
A flag for the case in which samples are in rows and variables/genes in columns. Defaults to FALSE. |

`balance_classes` |
Balances number of instances in the target vector y by sampling the number of instances in the minor class from all others. The number of samplings is controlled by resampling_number. Defaults to FALSE. |

Obs: For gene expression, you will need to run discretize_exprs first

Returns a data frame with the selected features index (first row) and their symmetrical uncertainty values regarding the class (second row). Variable names are present in rownames

1 2 3 4 5 6 7 8 | ```
data(scDengue)
exprs <- SummarizedExperiment::assay(scDengue, 'logcounts')
discrete_expression <- as.data.frame(discretize_exprs(exprs))
head(discrete_expression[,1:4])
infection <- SummarizedExperiment::colData(scDengue)
target <- infection$infection
fcbf(discrete_expression,target, thresh = 0.05, verbose = TRUE)
fcbf(discrete_expression,target, n_genes = 100)
``` |

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