|
|
--- |
|
|
license: cc0-1.0 |
|
|
--- |
|
|
|
|
|
## Dataset Summary |
|
|
The Iris dataset is a well-known dataset in machine learning and statistics, first introduced by Ronald Fisher in 1936. It contains 150 observations of iris flowers, categorized into three species: setosa, versicolor, and virginica. Each observation has four numerical features representing the dimensions of the flowers. |
|
|
|
|
|
## Usage |
|
|
This dataset is commonly used for classification tasks, benchmarking machine learning algorithms, and educational purposes. It is available in the Scikit-learn library and other sources. |
|
|
|
|
|
## Features |
|
|
- **sepal_length** (*float32*): Length of the sepal in cm. |
|
|
- **sepal_width** (*float32*): Width of the sepal in cm. |
|
|
- **petal_length** (*float32*): Length of the petal in cm. |
|
|
- **petal_width** (*float32*): Width of the petal in cm. |
|
|
- **label** (*string*): Species of the iris flower (setosa, versicolor, virginica). |
|
|
|
|
|
## Splits |
|
|
The dataset consists of a single split with all 150 samples available for training. |
|
|
|
|
|
## License |
|
|
The Iris dataset is in the public domain and can be used freely under the CC0-1.0 license. |
|
|
|
|
|
## Citation |
|
|
If using this dataset, please cite the original source: |
|
|
> Fisher, R.A. (1936). The use of multiple measurements in taxonomic problems. *Annals of Eugenics*, 7(2), 179-188. |
|
|
|
|
|
## Source |
|
|
- [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/iris) |
|
|
- [Scikit-learn](https://scikit-learn.org/stable/auto_examples/datasets/plot_iris_dataset.html) |
