File size: 1,464 Bytes
b0a9609 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 |
---
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) |