fashion_train: Fashion MNIST data

In m-clark/noiris: Data sets

Description

From the Kaggle entry: Fashion-MNIST is a dataset of Zalando's article images consisting of a training set of 60,000 examples (fashion_train)and a test set of 10,000 examples (fashion_test). Each example is a 28x28 grayscale image, associated with a label from 10 classes. Zalando intends Fashion-MNIST 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.

Usage

fashion_train

Format

A standard data frame with the following columns:

label

Image label. See details.

pixel1:pixel784

Grayscale value 0-255

Details

Basically this provides some entry level image classification that is a little more interesting than handwritten digits. Each image is 28 pixels in height and 28 pixels in width, for a total of 784 pixels in total when 'unrolled'. Each pixel has a single value associated with it (integer between 0 and 255), indicating the lightness or darkness of that pixel, with higher numbers meaning darker. The link below has downloadable image files. The labels are as follows:

0

T-shirt/top

1

Trouser

2

Pullover

3

Dress

4

Coat

5

Sandal

6

Shirt

7

Sneaker

8

Bag

9

Ankle boot

Note

License: The MIT License (MIT) Copyright © [2017] Zalando SE, https://tech.zalando.com

Source

Data set and info: https://www.kaggle.com/zalando-research/fashionmnist/version/4. More detail can be found at the GitHub repo.

Examples

library(noiris)
str(fashion_train)
str(fashion_test)

m-clark/noiris documentation built on Sept. 9, 2019, 9:08 a.m.