# iris

<br />

- **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](https://paperswithcode.com/dataset/iris-1)

- **Homepage** :
  <https://archive.ics.uci.edu/ml/datasets/iris>

- **Source code** :
  [`tfds.structured.Iris`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/structured/iris.py)

- **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](https://www.tensorflow.org/datasets/performances#auto-caching)):
  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](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):
  `('features', 'label')`

- **Figure**
  ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):
  Not supported.

- **Examples**
  ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):

<button id="displaydataframe">Display examples...</button>

- **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"
    }