iris

• Description:

This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is referenced frequently to this day. (See Duda & Hart, for example.) The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly separable from each other.

• Additional Documentation: Explore on Papers With Code

• Homepage: https://archive.ics.uci.edu/ml/datasets/iris

• Source code: tfds.structured.Iris

• Versions:

  • 2.0.0: New split API (https://tensorflow.org/datasets/splits)
  • 2.1.0 (default): Updated broken link

• Download size: 3.65 KiB

• Dataset size: 7.62 KiB

• Auto-cached (documentation): Yes

• Splits:

Split	Examples
'train'	150

• Feature structure:

FeaturesDict({
    'features': Tensor(shape=(4,), dtype=float32),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=3),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
features	Tensor	(4,)	float32
label	ClassLabel		int64

• Supervised keys (See as_supervised doc): ('features', 'label')

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@misc{Dua:2019 ,
author = "Dua, Dheeru and Graff, Casey",
year = "2017",
title = "{UCI} Machine Learning Repository",
url = "http://archive.ics.uci.edu/ml",
institution = "University of California, Irvine, School of Information and Computer Sciences"
}