4 datasets found

  1. Iris dataset uci

    • kaggle.com
    Updated Nov 6, 2021
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    Jillani Soft Tech (2021). Iris dataset uci [Dataset]. https://www.kaggle.com/datasets/jillanisofttech/iris-dataset-uci/code
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 6, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Jillani Soft Tech
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository.

    It includes three iris species with 50 samples each as well as some properties about each flower. One flower species is linearly separable from the other two, but the other two are not linearly separable from each other.

    The columns in this dataset are:

    Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species

  2. h

    my_iris

    • huggingface.co
    Updated Sep 20, 2024
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    Ralf Beier (2024). my_iris [Dataset]. https://huggingface.co/datasets/beierr1/my_iris
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 20, 2024
    Authors
    Ralf Beier
    License

    https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

    Description

    Iris Species Dataset

    The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository. It includes three iris species with 50 samples each as well as some properties about each flower. One flower species is linearly separable from the other two, but the other two are not linearly separable from each other. The dataset is taken from UCI Machine Learning Repository's… See the full description on the dataset page: https://huggingface.co/datasets/beierr1/my_iris.

  3. h

    iris

    • huggingface.co
    Updated Sep 23, 2022
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    scikit-learn (2022). iris [Dataset]. https://huggingface.co/datasets/scikit-learn/iris
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 23, 2022
    Dataset authored and provided by
    scikit-learn
    License

    https://choosealicense.com/licenses/cc0-1.0/https://choosealicense.com/licenses/cc0-1.0/

    Description

    Iris Species Dataset

    The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository. It includes three iris species with 50 samples each as well as some properties about each flower. One flower species is linearly separable from the other two, but the other two are not linearly separable from each other. The dataset is taken from UCI Machine Learning Repository's… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/iris.

  4. Iris Species

    • kaggle.com
    zip
    Updated Sep 27, 2016
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    UCI Machine Learning (2016). Iris Species [Dataset]. https://www.kaggle.com/datasets/uciml/iris
    Explore at:
    zip(3687 bytes)Available download formats
    Dataset updated
    Sep 27, 2016
    Dataset authored and provided by
    UCI Machine Learning
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository.

    It includes three iris species with 50 samples each as well as some properties about each flower. One flower species is linearly separable from the other two, but the other two are not linearly separable from each other.

    The columns in this dataset are:

    • Id
    • SepalLengthCm
    • SepalWidthCm
    • PetalLengthCm
    • PetalWidthCm
    • Species

    Sepal Width vs. Sepal Length

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Jillani Soft Tech (2021). Iris dataset uci [Dataset]. https://www.kaggle.com/datasets/jillanisofttech/iris-dataset-uci/code
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Iris dataset uci

Iris Dataset From Usi Machine Learning

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36 scholarly articles cite this dataset (View in Google Scholar)
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Nov 6, 2021
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Jillani Soft Tech
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Description

The Iris dataset was used in R.A. Fisher's classic 1936 paper, The Use of Multiple Measurements in Taxonomic Problems, and can also be found on the UCI Machine Learning Repository.

It includes three iris species with 50 samples each as well as some properties about each flower. One flower species is linearly separable from the other two, but the other two are not linearly separable from each other.

The columns in this dataset are:

Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species

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