R: Control Parameters for the Tune Function

tune.control {e1071} | R Documentation

## Control Parameters for the Tune Function

### Description

Creates an object of class `tune.control` to be used with the `tune` function, containing various control parameters.

### Usage

    tune.control(random = FALSE, nrepeat = 1, repeat.aggregate = mean,
    sampling = c("cross", "fix", "bootstrap"), sampling.aggregate = mean,
    sampling.dispersion = sd,
    cross = 10, fix = 2/3, nboot = 10, boot.size = 9/10, best.model = TRUE,
    performances = TRUE, error.fun = NULL)

### Arguments

`random` | if an integer value is specified, `random` parameter vectors are drawn from the parameter space.
`nrepeat` | specifies how often training shall be repeated.
`repeat.aggregate` | function for aggregating the repeated training results.
`sampling` | sampling scheme. If `sampling = "cross"`, a `cross`-times cross validation is performed. If `sampling = "boot"`, `nboot` training sets of size `boot.size` (part) are sampled (with replacement) from the supplied data. If `sampling = "fix"`, a single split into training/validation set is used, the training set containing a `fix` part of the supplied data. Note that a separate validation set can be supplied via `validation.x` and `validation.y`. It is only used for `sampling = "boot"` and `sampling = "fix"`; in the latter case, `fix` is set to 1.
`sampling.aggregate,sampling.dispersion` | functions for aggregating the training results on the generated training samples (default: mean and standard deviation).
`cross` | number of partitions for cross-validation.
`fix` | part of the data used for training in fixed sampling.
`nboot` | number of bootstrap replications.
`boot.size` | size of the bootstrap samples.
`best.model` | if `TRUE`, the best model is trained and returned (the best parameter set is used for training on the complete training set).
`performances` | if `TRUE`, the performance results for all parameter combinations are returned.
`error.fun` | function returning the error measure to be minimized. It takes two arguments: a vector of true values and a vector of predicted values. If `NULL`, the misclassification error is used for categorical predictions and the mean squared error for numeric predictions.

### Value

An object of class `"tune.control"` containing all the above parameters (either the defaults or the user specified values).

### Author(s)

David Meyer
David.Meyer@R-project.org

### See Also

`tune`

[Package e1071 version 1.7-6 Index]