iris
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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.
Split |
Examples |
'train' |
150 |
FeaturesDict({
'features': Tensor(shape=(4,), dtype=float32),
'label': ClassLabel(shape=(), dtype=int64, num_classes=3),
})
Feature |
Class |
Shape |
Dtype |
Description |
|
FeaturesDict |
|
|
|
features |
Tensor |
(4,) |
float32 |
|
label |
ClassLabel |
|
int64 |
|
@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"
}
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Last updated 2023-09-09 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2023-09-09 UTC."],[],[],null,["# iris\n\n\u003cbr /\u003e\n\n- **Description**:\n\nThis is perhaps the best known database to be found in the pattern recognition\nliterature. Fisher's paper is a classic in the field and is referenced\nfrequently to this day. (See Duda \\& Hart, for example.) The data set contains 3\nclasses of 50 instances each, where each class refers to a type of iris plant.\nOne class is linearly separable from the other 2; the latter are NOT linearly\nseparable from each other.\n\n- **Additional Documentation** :\n [Explore on Papers With Code\n north_east](https://paperswithcode.com/dataset/iris-1)\n\n- **Homepage** :\n \u003chttps://archive.ics.uci.edu/ml/datasets/iris\u003e\n\n- **Source code** :\n [`tfds.structured.Iris`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/structured/iris.py)\n\n- **Versions**:\n\n - `2.0.0`: New split API (\u003chttps://tensorflow.org/datasets/splits\u003e)\n - **`2.1.0`** (default): Updated broken link\n- **Download size** : `3.65 KiB`\n\n- **Dataset size** : `7.62 KiB`\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n Yes\n\n- **Splits**:\n\n| Split | Examples |\n|-----------|----------|\n| `'train'` | 150 |\n\n- **Feature structure**:\n\n FeaturesDict({\n 'features': Tensor(shape=(4,), dtype=float32),\n 'label': ClassLabel(shape=(), dtype=int64, num_classes=3),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|----------|--------------|-------|---------|-------------|\n| | FeaturesDict | | | |\n| features | Tensor | (4,) | float32 | |\n| label | ClassLabel | | int64 | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `('features', 'label')`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n Not supported.\n\n- **Examples**\n ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\n- **Citation**:\n\n @misc{Dua:2019 ,\n author = \"Dua, Dheeru and Graff, Casey\",\n year = \"2017\",\n title = \"{UCI} Machine Learning Repository\",\n url = \"http://archive.ics.uci.edu/ml\",\n institution = \"University of California, Irvine, School of Information and Computer Sciences\"\n }"]]