FIT: make.recipe – R documentation

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FIT

make.recipe

Creates a recipe for training models.

Description

Creates a recipe for training models.

Usage

make.recipe(envs, init, optim, fit, init.data, time.step, gate.open.min = 0,
  opts = NULL)

Arguments

`envs`	An array of weather factors to be taken into account during the construction of models. At the moment, the array `envs` can only contain a single weather factor from `weather.entries`, though there is a plan to remove the restriction in a future version.
`init`	A string to specify the method to choose the initial parameters. (One of `'gridsearch'` or `'manual'`.)
`optim`	A string to specify the method to be used for optimizing the model parameters. (One of `'none'`, `'lm'` or `'lasso'`)
`fit`	A string to specify the method to be used for fixing the linear regression coefficients. (One of `'fit.lm'` or `'fit.lasso'`.)
`init.data`	Auxiliary data needed to perform the Init stage using the method specified by the `init` argument. When `init` is `'gridsearch'`, it should be a list representing a discretized parameter space. When `init` is `'manual'`, it should be a list of parameter values that is used as the initial values for the parameters in the Optim stage.
`time.step`	An integer to specify the basic unit of time (in minute) for the transcriptomic models. Must be a multiple of the time step of weather data.
`gate.open.min`	The minimum opning length in minutes of the gate function for environmental inputs.
`opts`	An optional named list that specifies the arguments to be passed to methods that constitute each stage of the model training. Each key of the list corresponds to a name of a method. See examples for the supported options.

Value

An object representing the procedure to construct models.

Examples

## Not run: 
init.params <- .. # choose them wisely
# Defined in Train.R:
# default.opts <- list(
#   none  = list(),
#   lm    = list(maxit=1500, nfolds=-1), # nfolds for lm is simply ignored
#   lasso = list(maxit=1000, nfolds=10)
# )
recipe <- FIT::make.recipe(c('wind', 'temperature'),
                           init = 'manual',
                           init.data = init.params,
                           optim = c('lm', 'none', 'lasso'),
                           fit = 'fit.lasso',
                           time.step = 10,
                           opts =
                             list(lm    = list(maxit = 900),
                                  lasso = list(maxit = 1000)))

## End(Not run)

FIT

Transcriptomic Dynamics Models in Field Conditions

v0.0.6

MPL (>= 2) | file LICENSE

Authors

Koji Iwayama [cre], Yuri Aisaka [aut]

Initial release