% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tSNE_class.R
\name{tSNE}
\alias{tSNE}
\title{tSNE}
\usage{
tSNE(
  dims = 2,
  perplexity = 30,
  max_iter = 100,
  theta = 0.5,
  check_duplicates = FALSE,
  init = NULL,
  eta = 200,
  ...
)
}
\arguments{
\item{dims}{(numeric) The number of tSNE dimensions computed. The default is \code{2}.\cr}

\item{perplexity}{(numeric) Perplexity parameter. The default is \code{30}.\cr}

\item{max_iter}{(numeric) The maximum number of tSNE iterations. The default is \code{100}.\cr}

\item{theta}{(numeric) Speed/accuracy trade-off. A value of 0 gives an exact tSNE. The default is \code{0.5}.\cr}

\item{check_duplicates}{(logical) Check for duplicates. Allowed values are limited to the following: \itemize{ \item{\code{"TRUE"}: Checks for the presence of exact duplicate samples.}\item{\code{"FALSE"}: Does not check for exact duplicate samples.}} The default is \code{FALSE}.\cr}

\item{init}{(NULL, data.frame, DatasetExperiment) A set of coordinates for initialising the tSNE algorithm. NULL uses random initialisation. The default is \code{NULL}.}

\item{eta}{(numeric) The learning rate parameter. The default is \code{200}.\cr}

\item{...}{Additional slots and values passed to \code{struct_class}.}
}
\value{
A  \code{tSNE} object with the following \code{output} slots:
\tabular{ll}{
\code{Y} \tab          (DatasetExperiment)  \cr
}
}
\description{
t-Distributed Stochastic Neighbor Embedding.
}
\details{
This object makes use of functionality from the following packages:\itemize{  \item{\code{Rtsne}}}
}
\section{Inheritance}{

A \code{tSNE} object inherits the following \code{struct} classes: \cr\cr
\verb{[tSNE]} >> \verb{[model]} >> \verb{[struct_class]}
}

\examples{
M = tSNE(
      dims = 2,
      perplexity = 30,
      max_iter = 1000,
      theta = 0.5,
      check_duplicates = FALSE,
      init = NULL,
      eta = 200)

M = tSNE()

}
\references{
Krijthe JH (2015). \emph{Rtsne: T-Distributed Stochastic Neighbor Embedding
using Barnes-Hut Implementation}. R package version 0.17,
\url{https://github.com/jkrijthe/Rtsne}.

van der Maaten L, Hinton G (2008). "Visualizing High-Dimensional Data
Using t-SNE." \emph{Journal of Machine Learning Research}, \emph{9}, 2579-2605.

van der Maaten L (2014). "Accelerating t-SNE using Tree-Based
Algorithms." \emph{Journal of Machine Learning Research}, \emph{15}, 3221-3245.
}