% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/featured_space.R
\name{maxent_predict_model}
\alias{maxent_predict_model}
\title{Predict with a Trained MaxEnt Model}
\usage{
maxent_predict_model(featured_space, newdata)
}
\arguments{
\item{featured_space}{External pointer to a trained FeaturedSpace object.}

\item{newdata}{Numeric matrix: one row per new point, one column per
feature.  Column values must be the \emph{already-evaluated} feature
values (e.g., from running \code{maxent_feature_eval()} for each feature
and each point).}
}
\value{
Numeric vector of raw (unnormalized) prediction scores.
}
\description{
Computes raw Gibbs distribution scores for new environmental data, using
the feature lambdas stored in the trained FeaturedSpace.
}
\examples{
\donttest{
# After training, predict on 5 new points with 2 features each
newdata <- matrix(runif(10), nrow = 5, ncol = 2)
preds <- maxent_predict_model(fs, newdata)
}
}
