150 labeled samples of iris flowers across 3 species: Setosa, Versicolour, and Virginica. Each entry provides 4 numeric measurements including sepal and petal dimensions in centimeters.
Use Cases
- Train a support vector machine (SVM) to classify the species label based on the four measurement features
- Apply K-Means clustering to the sepal and petal columns to evaluate unsupervised learning performance
- Generate a correlation matrix between sepal_width and petal_width to identify feature dependencies
- Evaluate the accuracy of a decision tree classifier using the species target column
Strengths
- 150 rows of data with a balanced distribution of 50 samples per species
- 4 continuous numeric features: sepal_length, sepal_width, petal_length, and petal_width
- 3 categorical target labels representing specific Iris species
- Measurements provided as continuous float values in centimeters