% Generated by roxygen2: do not edit by hand

% Please edit documentation in R/ich_predict.R

\name{ich_predict}

\alias{ich_predict}

\title{Predict ICH Images}

\usage{

ich_predict(

  df,

  nim,

  model = c("rf", "logistic", "big_rf"),

  verbose = TRUE,

  native = TRUE,

  native_img = NULL,

  transformlist = NULL,

  interpolator = NULL,

  native_thresh = 0.5,

  shiny = FALSE,

  model_list = NULL,

  smoothed_cutoffs = NULL,

  outfile = NULL,

  ...

)

}

\arguments{

\item{df}{\code{\link{data.frame}} of predictors.  If \code{multiplier}

column does not exist, then \code{\link{ich_candidate_voxels}} will

be called}

\item{nim}{object of class \code{\link{nifti}}, from

\code{\link{make_predictors}}}

\item{model}{model to use for prediction,

either the random forest (rf) or logistic}

\item{verbose}{Print diagnostic output}

\item{native}{Should native-space predictions be given?}

\item{native_img}{object of class \code{\link{nifti}}, which

is the dimensions of the native image}

\item{transformlist}{Transforms list for the transformations back to native space.

NOTE: these will be inverted.}

\item{interpolator}{Interpolator for the transformation back to native space}

\item{native_thresh}{Threshold for re-thresholding binary mask after

interpolation}

\item{shiny}{Should shiny progress be called?}

\item{model_list}{list of model objects, used mainly for retraining

but only expert use.}

\item{smoothed_cutoffs}{A list with an element

\code{mod.dice.coef}, only expert use.}

\item{outfile}{filename for output file.

We write the smoothed, thresholded image.  If \code{native = TRUE},

then the file will be native space, otherwise in registered

space}

\item{...}{Additional options passsed to \code{\link{ich_preprocess}}}

}

\value{

List of output registered and native space

prediction/probability images

}

\description{

This function will take the data.frame of predictors and

predict the ICH voxels from the model chosen.

}

\seealso{

\code{\link{ich_candidate_voxels}}

}