dataset_fashion_mnist.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/datasets.R
\name{dataset_fashion_mnist}
\alias{dataset_fashion_mnist}
\title{Fashion-MNIST database of fashion articles}
\usage{
dataset_fashion_mnist(convert = TRUE)
}
\arguments{
\item{convert}{When \code{TRUE} (default) the datasets are returned as R arrays.
If \code{FALSE}, objects are returned as NumPy arrays.}
}
\value{
Lists of training and test data: \verb{train$x, train$y, test$x, test$y}, where
\code{x} is an array of grayscale image data with shape (num_samples, 28, 28) and \code{y}
is an array of article labels (integers in range 0-9) with shape (num_samples).

\if{html}{\out{<div class="sourceCode r">}}\preformatted{str(dataset_fashion_mnist())
}\if{html}{\out{</div>}}

\if{html}{\out{<div class="sourceCode">}}\preformatted{## List of 2
##  $ train:List of 2
##   ..$ x: int [1:60000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
##   ..$ y: int [1:60000(1d)] 9 0 0 3 0 2 7 2 5 5 ...
##  $ test :List of 2
##   ..$ x: int [1:10000, 1:28, 1:28] 0 0 0 0 0 0 0 0 0 0 ...
##   ..$ y: int [1:10000(1d)] 9 2 1 1 6 1 4 6 5 7 ...

}\if{html}{\out{</div>}}

\if{html}{\out{<div class="sourceCode r">}}\preformatted{str(dataset_fashion_mnist(convert = FALSE))
}\if{html}{\out{</div>}}

\if{html}{\out{<div class="sourceCode">}}\preformatted{## List of 2
##  $ train:List of 2
##   ..$ x: <numpy.ndarray shape(60000,28,28), dtype=uint8>
##   ..$ y: <numpy.ndarray shape(60000), dtype=uint8>
##  $ test :List of 2
##   ..$ x: <numpy.ndarray shape(10000,28,28), dtype=uint8>
##   ..$ y: <numpy.ndarray shape(10000), dtype=uint8>

}\if{html}{\out{</div>}}
}
\description{
Dataset of 60,000 28x28 grayscale images of the 10 fashion article classes,
along with a test set of 10,000 images. This dataset can be used as a drop-in
replacement for MNIST. The class labels are encoded as integers from 0-9 which
correspond to T-shirt/top, Trouser, Pullover, Dress, Coat, Sandal, Shirt,
}
\details{
Dataset of 60,000 28x28 grayscale images of 10 fashion categories,
along with a test set of 10,000 images. This dataset can be used as a drop-in
replacement for MNIST. The class labels are:
\itemize{
\item 0 - T-shirt/top
\item 1 - Trouser
\item 2 - Pullover
\item 3 - Dress
\item 4 - Coat
\item 5 - Sandal
\item 6 - Shirt
\item 7 - Sneaker
\item 8 - Bag
\item 9 - Ankle boot
}
}
\seealso{
Other datasets: \cr
\code{\link{dataset_boston_housing}()} \cr
\code{\link{dataset_california_housing}()} \cr
\code{\link{dataset_cifar10}()} \cr
\code{\link{dataset_cifar100}()} \cr
\code{\link{dataset_imdb}()} \cr
\code{\link{dataset_mnist}()} \cr
\code{\link{dataset_reuters}()} \cr
}
\concept{datasets}