Iris dataset

"Exploring Patterns: The Iris Dataset Analysis"

The Iris dataset is a classic dataset in the field of machine learning and statistics.
It was introduced by the British statistician and biologist Ronald Fisher in his 1936 paper "The use of multiple measurements in taxonomic problems" as an example of linear discriminant analysis.
The dataset consists of 150 samples of iris flowers, each belonging to one of three species: Setosa, Versicolor, and Virginica.

Columns : -

• Sepal Length (cm): The length of the sepal, which is the outermost part of the flower that protects the petals.
• Sepal Width (cm): The width of the sepal, measured at its widest point.
• Petal Length (cm): The length of the petal, which is the colorful inner part of the flower.
• Petal Width (cm): The width of the petal, measured at its widest point.
• Species: The species of iris flower, which can be one of three classes: Setosa, Versicolor, or Virginica.

These columns provide measurements of various parts of the iris flower, along with the corresponding species labels, making it a versatile dataset for analysis and classification tasks.