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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/spruce.R
\name{spruce}
\alias{spruce}
\alias{spruce_numeric}
\alias{spruce_class}
\alias{spruce_prob}
\title{Spruce up predictions}
\usage{
spruce_numeric(pred)
spruce_class(pred_class)
spruce_prob(pred_levels, prob_matrix)
}
\arguments{
\item{pred}{(\code{type = "numeric"}) A numeric vector of predictions.}
\item{pred_class}{(\code{type = "class"}) A factor of "hard" class predictions.}
\item{pred_levels, prob_matrix}{(\code{type = "prob"})
\itemize{
\item \code{pred_levels} should be a character vector of the original levels of
the outcome used in training.
\item \code{prob_matrix} should be a numeric matrix of class probabilities with
as many columns as levels in \code{pred_levels}, and in the same order.
}}
}
\value{
A tibble, ideally with the same number of rows as the \code{new_data} passed
to \code{predict()}. The column names and number of columns vary based on the
function used, but are standardized.
}
\description{
The family of \verb{spruce_*()} functions convert predictions into a
standardized format. They are generally called from a prediction
implementation function for the specific \code{type} of prediction to return.
}
\details{
After running a \verb{spruce_*()} function, you should \emph{always} use the validation
function \code{validate_prediction_size()} to ensure that the number of rows
being returned is the same as the number of rows in the input (\code{new_data}).
}
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