The Iris dataset is a classic in machine learning, containing 150 samples of iris flowers with 4 features (sepal length, sepal width, petal length, petal width) and 3 classes (Setosa, Versicolor, Virginica). Here’s how to visualize it effectively:
📊 Key Visualization Techniques
- Scatter Plot
Plot features against each other to observe class separation. - Pair Plot
A matrix of scatter plots showing pairwise relationships. - Heatmap
Highlight correlations between features using color gradients.
🧪 Example Code (Python)
import seaborn as sns
sns.set(style="ticks")
iris = sns.load_dataset("iris")
sns.pairplot(iris, hue="species")
Run this code to generate interactive visualizations.
📚 Extend Your Knowledge
Let me know if you need help with specific visualizations! 📈