% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/nmfae.signed.R
\name{predict.nmfae.signed}
\alias{predict.nmfae.signed}
\title{Predict method for nmfae.signed}
\usage{
\method{predict}{nmfae.signed}(object, newY2 = NULL, Y1 = NULL, type = c("response", "class"), ...)
}
\arguments{
\item{object}{A fitted \code{"nmfae.signed"} object.}

\item{newY2}{New input matrix (P2 x N_new).  If \code{NULL}, returns
the training fitted values.}

\item{Y1}{Optional reference Y1 for scatter / confusion plot.}

\item{type}{Output: \code{"response"} (raw signed) or \code{"class"}.}

\item{...}{Unused.}
}
\value{
A numeric matrix (\code{"response"}) or factor (\code{"class"}).
}
\description{
Computes \eqn{\hat Y_1 = X_1 (C_{+} - C_{-}) X_2 Y_2^{\mathrm{new}}}.
Since \eqn{\Theta = C_{+} - C_{-}} is signed, predictions may contain
negative entries even when \eqn{Y_1 \ge 0} in training.
}
\section{Lifecycle}{

This function is \strong{experimental}. The interface may change in
future versions.
}

\references{
Ding, C. H. Q., Li, T., & Jordan, M. I. (2010). Convex and
semi-nonnegative matrix factorizations. \emph{IEEE Transactions on
Pattern Analysis and Machine Intelligence}, 32(1), 45--55.
}
\seealso{
\code{\link{nmfae.signed}}
}
