Description Usage Arguments Value Author(s) Examples

Define feature combinations, and fetch additional information about each unique combination

1 2 3 4 5 6 | ```
feature_combinations(
m,
exact = TRUE,
n_combinations = 200,
weight_zero_m = 10^6
)
``` |

`m` |
Positive integer. Total number of features. |

`exact` |
Logical. If |

`n_combinations` |
Positive integer. Note that if |

`weight_zero_m` |
Numeric. The value to use as a replacement for infinite combination weights when doing numerical operations. |

A data.table that contains the following columns:

- id_combination
Positive integer. Represents a unique key for each combination. Note that the table is sorted by

`id_combination`

, so that is always equal to`x[["id_combination"]] = 1:nrow(x)`

.- features
List. Each item of the list is an integer vector where

`features[[i]]`

represents the indices of the features included in combination`i`

. Note that all the items are sorted such that`features[[i]] == sort(features[[i]])`

is always true.- n_features
Vector of positive integers.

`n_features[i]`

equals the number of features in combination`i`

, i.e.`n_features[i] = length(features[[i]])`

.

.

- N
Positive integer. The number of unique ways to sample

`n_features[i]`

features from`m`

different features, without replacement.

Nikolai Sellereite, Martin Jullum

1 2 3 4 5 6 | ```
# All combinations
x <- feature_combinations(m = 3)
nrow(x) # Equals 2^3 = 8
# Subsample of combinations
x <- feature_combinations(exact = FALSE, m = 10, n_combinations = 1e2)
``` |

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