Description Usage Arguments Details Value Author(s) See Also Examples

This translates the `sampsize`

argument to `gensemble`

to a form for use internally.

1 | ```
mksampsize(Y, sampsize = NULL, proportion = FALSE)
``` |

`Y` |
The response vector. |

`sampsize` |
The desired sample size(s). Can be NULL, a single value, a vector or a list. See the details section for more information. |

`proportion` |
A |

For regression, `sampsize`

indicates how much of the underlying data should be used in the bagged model. It should either be `NULL`

or a single value. If it is `NULL`

, roughly 80

For classification, the internals of `gensemble`

require a list of each class and the size of the sample from each class. If `sampsize`

is `NULL`

, this list will be built using the levels present in `Y`

, and roughly 80

If `Y`

is a factor, will return a list of each class and the number of data points to sample for that class. Otherwise it will return a single value.

Peter Werner <gensemble.r@gmail.com>

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
#regression
Y <- trees[,3]
#use roughly 80% for each training iteration
mksampsize(Y)
#the same thing using proportion
mksampsize(Y, 0.8, TRUE)
#classification
Y <- iris[,5]
#use rougly 80% of each class
mksampsize(Y)
#specifiy the size of each class in absolute terms
mksampsize(Y, list(setosa=20, versicolor=30, virginica=40))
#use about 70% of each class
mksampsize(Y, 0.7, proportion=TRUE)
#specifiy the proportion for each class
mksampsize(Y, c(0.5, 0.6, 0.7), proportion=TRUE)
``` |

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