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Fishers Iris Species Dataset
Data Science and Analytics
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About
This dataset is a classic in machine learning, famously used by R.A. Fisher in his 1936 paper, "The Use of Multiple Measurements in Taxonomic Problems." It contains measurements for three distinct species of iris flowers, with fifty samples for each species. Each sample includes properties about the flower, such as sepal and petal dimensions. The dataset is particularly notable because one of the flower species is linearly separable from the other two, while the remaining two species are not linearly separable from each other, making it an excellent resource for exploring classification algorithms. It is widely available on the UCI Machine Learning Repository.
Columns
- Id: A unique identifier for each entry in the dataset.
- SepalLengthCm: The length of the sepal in centimetres.
- SepalWidthCm: The width of the sepal in centimetres.
- PetalLengthCm: The length of the petal in centimetres.
- PetalWidthCm: The width of the petal in centimetres.
- Species: The species of iris flower, representing the target variable for classification tasks.
Distribution
The dataset is provided in a CSV format, specifically
Iris.csv, with a file size of 5.11 kB. It consists of 6 columns and contains 150 valid records. There are no missing values across any of the columns, ensuring a clean and ready-to-use dataset. The 'Species' column features 3 unique values, with 'Iris-setosa' being the most frequent, accounting for 33% of the samples.Usage
This dataset is ideal for various machine learning applications, particularly those focused on classification. It is a perfect starting point for:
- Developing and testing new classification algorithms.
- Learning about linear and non-linear separability in data.
- Practising data preprocessing and feature engineering.
- Visualising data distributions and relationships using tools like Matplotlib.
- Implementing foundational machine learning models with libraries such as NumPy and scikit-learn (sklearn).
Coverage
The dataset focuses on three specific iris species, with 50 samples collected for each. It contains morphological measurements (sepal and petal dimensions) for these flowers. The original context dates back to R.A. Fisher's 1936 paper. There are no specific geographic, time range, or demographic notes provided, as it is a biological dataset primarily concerned with species classification.
License
CC0: Public Domain
Who Can Use It
This dataset is well-suited for a broad audience, including:
- Machine Learning Enthusiasts: For hands-on experience with a foundational classification problem.
- Students and Educators: An excellent pedagogical tool for teaching concepts like data exploration, classification, and model evaluation.
- Researchers: To benchmark new algorithms or explore taxonomic problems with a well-established dataset.
- Data Scientists: For quick prototyping, learning new libraries, or creating illustrative examples of data analysis.
Dataset Name Suggestions
- Iris Flower Measurements
- Fisher's Iris Species Dataset
- Botanical Iris Classification Data
- Machine Learning Iris Dataset
- UCI Iris Dataset for Classification
Attributes
Original Data Source: Fishers Iris Species Dataset
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