Fashion-MNIST
OpenML dataset with id 40996
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Full work available at URL: https://api.openml.org/data/v1/download/18238735/Fashion-MNIST.arff
Upload date: 20 December 2017
Dataset Characteristics
Number of classes: 10
Number of features: 785 (numeric: 784, symbolic: 1 and in total binary: 0 )
Number of instances: 70,000
Number of instances with missing values: 0
Number of missing values: 0
Author: Han Xiao, Kashif Rasul, Roland Vollgraf Source: Zalando Research Please cite: Han Xiao and Kashif Rasul and Roland Vollgraf, Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms, arXiv, cs.LG/1708.07747
Fashion-MNIST is a dataset of Zalando's article images, consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. Fashion-MNIST is intended to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.
Raw data available at: https://github.com/zalandoresearch/fashion-mnist
Target classes
Each training and test example is assigned to one of the following labels:
Label Description
0 T-shirt/top
1 Trouser
2 Pullover
3 Dress
4 Coat
5 Sandal
6 Shirt
7 Sneaker
8 Bag
9 Ankle boot
This page was built for dataset: Fashion-MNIST
